South Korea joined SNOMED International as the 39th member country. To ensure semantic interoperability, South Korea introduced SNOMED CT  in 2020. However, there is no methodology to map local Korean terms to SNOMED CT. Instead, this is performed sporadically and independently at each local medical institution. The quality of the mapping, therefore, cannot be guaranteed.This study aimed to develop and introduce a guideline to map local Korean terms to the SNOMED CT used to document clinical findings and procedures in electronic health records at health care institutions in South Korea.The guidelines were developed from December 2020 to December 2022. An extensive literature review was conducted. The overall structures and contents of the guidelines with diverse use cases were developed by referencing the existing SNOMED CT mapping guidelines, previous studies related to SNOMED CT mapping, and the experiences of the committee members. The developed guidelines were validated by a guideline review panel.The SNOMED CT mapping guidelines developed in this study recommended the following 9 steps: define the purpose and scope of the map, extract terms, preprocess source terms, preprocess source terms using clinical context, select a search term, use search strategies to find SNOMED CT concepts using a browser, classify mapping correlations, validate the map, and build the final map format.The guidelines developed in this study can support the standardized mapping of local Korean terms into SNOMED CT. Mapping specialists can use this guideline to improve the mapping quality performed at individual local medical institutions. South Korea is a leader in global information and communication technology. According to a 2021 Organization for Economic Co-operation and Development (OECD) survey of national health data infrastructure and governance, South Korea ranked second among OECD countries on data availability, maturity, and use . This ocTo achieve semantic interoperability, interface or local terms extracted from natural language written by a health care provider can be stored as reference terminology, such as in the SNOMED CT . The stored terms with reference terminology can then be used in classification systems such as the International Classification of Diseases (ICD) for statistical purposes . Health Various efforts have mapped the terms used to document clinical findings and procedures in electronic medical records (EMRs), classification systems such as ICD 10th revision, and existing health care terminologies such as Logical Observation Identifiers Names and Codes (LOINC) and International Classification of Nursing Practice (ICNP) to the SNOMED CT in other countries -11. The Individual medical institutions have attempted to map their terms to SNOMED CT. However, the mapping quality cannot be guaranteed due to its sporadic and independent map development. SNOMED International introduced Snap2, a tool to support mapping. However, since the tool is based on English source terms, it is difficult to apply to the Korean terms used in South Korea. This study, therefore, aimed to develop a guideline to ensure high-quality mapping of terms used to document clinical findings and procedures in the EMRs of local institutions in South Korea to SNOMED CT. The guideline focuses on a process of defining a relationship between concepts used in EMRs and the concepts of SNOMED CT . The guiThe process of developing the mapping guideline was led by a mapping guideline development committee. The committee consisted of 3 mapping experts. All committee members had SNOMED CT mapping experiences spanning more than 5 years and have conducted various national projects, such as SNOMED CT mapping of KCD-7 and EDI codes supported by the Korea Health Information Service under the Ministry of Health and Welfare in South Korea. The development of the guidelines was conducted from December 2020 to December 2022.To develop the mapping guidelines, the committee members first developed an overall structure based on a review of the existing guidelines and their own mapping and teaching experiences. An extensive literature review was performed in PubMed, MEDLINE, and Google Scholar. The existing mapping guidelines and previous studies -24 were Based on the committee members’ experiences, the most difficult aspects of mapping between local terms and SNOMED CT were extracting and understanding the source terms, developing search terms, and searching the target SNOMED CT. However, the SNOMED CT-AU mapping guideline does not describe how to extract and understand source terms from EMRs, how to develop search terms, or how to search for target concepts using the SNOMED International browser. It is difficult for beginners to apply the existing SNOMED CT mapping guidelines, such as those of the SNOMED CT-AU. Therefore, the committee added 4 steps to the guideline: extract terms, preprocess source terms using clinical context, select a search term, and use search strategies to find SNOMED CT concepts using a browser.A guideline review panel was invited to validate the guideline from May 2021 to September 2022. The review panel consisted of 3 mapping experts: a professor with more than 5 years of SNOMED CT mapping experience working at a South Korean university and 2 mapping specialists with more than 3 years of mapping experience. The first author emailed, explaining the purpose of the study, and asked to review the understandability and usability of the developed guidelines and to add more mapping examples, if possible, to the panel. In addition, 2 graduate students with no mapping experience were asked to assess whether the guideline was understandable and helpful throughout the email. These 2 processes were repeated until no more issues were identified.The SNOMED CT mapping guidelines developed in this study consisted of 9 steps, as presented in To proceed with mapping, the mapping specialists must first define the purpose and scope. The purpose of the map can be for national health insurance claims, classification and statistics , knowledge management , health information exchange among institutions, studies , and patient care. The scope of the map refers to the range of source and target codes and granularity and may differ according to its purpose. For example, if the map’s purpose is to provide prevalence statistics for specific diseases, the source codes are restricted to KCD-7 in the clinical findings domain, and the range of target codes should be SNOMED CT concepts in the clinical findings, person, or event top-level hierarchy. If the map’s purpose is for national health insurance claims, the source codes are restricted to the EDI codes in the procedure domain, and the range of target codes should be SNOMED CT concepts in the procedures’ top-level hierarchy.Map granularity can also vary according to the purpose of the map. For example, if the map is for national health insurance claims, the local term “alcohol-related seizure,” mapped to KCD-7 code G40.5 , should be mapped to the abstract SNOMED CT concept 230431001 (situation-related seizures [disorder]). However, if the map is for exchanging health information among institutions, the source code should be mapped at the granular level to SNOMED CT concept 308742005 .When the purpose and scope of the map are determined, mapping specialists should extract terms from EMRs while considering where and how clinical notes are documented. Patient diagnoses can be extracted from progress notes and other similar information sources. Family and past medical histories can be extracted from progress notes and initial nursing assessment records. Surgical procedure names can be extracted from surgical notes. Evaluation procedures can be extracted from laboratory documentation.These data sources are either structured, semistructured, or unstructured medical records written in natural language; for example, as presented in step A of When conducting automatic term extraction through NLP, word segmentation throughout semantic analysis is required using a corpus ,34. For Alternatively, terms can simply be extracted from code systems such as KCD-7, EDI, and local hospital codes. In these cases, it is sufficient to extract the terms mapped to the code system without duplication.Preprocessing takes daily English terms as the source terms, for instance, by translating Korean terms into English. These Korean English (Konglish) terms are then translated into native English terms, with acronyms or abbreviations defined and spelling or punctuation errors corrected. If terms are written in Korean, preprocessing starts with translating the Korean terms into English. For example, “당뇨” written in Korean must be translated into “diabetes mellitus.” Konglish is often used in Korean clinical settings. It is necessary to change Konglish terms into proper English terms. In Korean clinical settings, for example, an evaluation procedure “초음파 검사” is represented by various English words such as in SONO and sonogram. SONO, or sonogram, is the image obtained using ultrasound. If it is the name of an evaluation procedure, it is, therefore, appropriate to translate it into “ultrasound.”If terms are written in acronyms or abbreviations, which are commonly used by health care providers, preprocessing may be required to rewrite them in complete words. The acronym ASD, used in departments of pediatric cardiology, was defined as “atrial septal defect.” The abbreviation MMG used frequently in South Korea, must be rewritten to “mammography.”Terms should be corrected when misspelled. For example, “asceding aorta dilatation” should be corrected to “ascending aorta dilatation” to obtain the correct search results. Furthermore, if terms include incorrect punctuation, it is preferable to edit the spacing of the source terms. For example, the search for the source term “DeQuervain's disease, wrist, Rt.” is missing a space, which must be added to produce “De Quervain.” Other examples are presented in step B of The terms preprocessed in the previous step can have different meanings depending on the clinical context, such as subject, temporal, or finding contexts. For example, the meaning of the preprocessed source term “diabetes mellitus” varies depending on which part of the EMR it is extracted from; it can be “diabetes mellitus,” “past medical history of diabetes mellitus,” “family history of diabetes mellitus,” or “no family history of diabetes mellitus.” “Past medical history of diabetes mellitus” means that the temporal context is in the past. “Family history of diabetes mellitus” means that the temporal context is current or in the past and that the subject is a person in the patient’s family. “No family history of diabetes mellitus” means that the temporal and subject contexts are the same as “family history of diabetes mellitus,” but the finding context is absent.Clinical context can be inferred from the source of the structured or semistructured medical records or the text in which the source term is written. If the family history section is the source of the medical record, the subject is a family member of the patient, and the temporal context is the past or the present. If the past medical history section is the source, the subject is the patient, and the temporal context is the past or present. If the chief complaint section is the source, the subject is the patient, and the temporal context is the present. If the clinical context cannot be inferred from the structured or semistructured records, the mapping personnel should read the text in which the source term is written. Examples are presented in step C of To search for a target SNOMED CT concept, a search term comprising keywords of the source terms that have undergone preprocessing must be selected. The search success rate is increased if the mapping specialist understands the general naming convention used by SNOMED International . For exaStop words in NLP, which are frequently used words with restricted semantic specificity, should be excluded from search terms to improve the success rate. These stop words include articles , prepositions , conjunctions , and ambiguous adjectives or adverbs . Examples are presented in step D of Searches can start with the first 3 characters of search terms. With the first 3 characters, the mapping specialist can prevent search failures due to differences in the forms of various words, such as nouns, verbs, and the use of the passive voices and differences in singular and passive voices. For example, if the source term “perforated small intestine” is entered into the browser, equivalently matched concepts cannot be obtained. However, if 3 characters of each word—“per sma int”—are entered, the concept “235741002 |Perforation of small intestine (disorder)|” is matched.When a SNOMED CT concept appears, the parent, child, and sibling concepts—higher, lower, or at the same level in the hierarchy—must be reviewed to determine if it is semantically correct.If the target SNOMED CT concept is not identified by search terms, synonyms should be used as search terms for the source term. The synonyms can be obtained by searching the medical terminology database released by the Korean Medical Association  or by seIf the SNOMED CT concept is not found with synonyms of search terms, the target concept that is semantically equivalent to the source term can be searched by starting with broader or narrower terms. For example, “IUD ectopic” in the diagnosis means that an intrauterine device is in an abnormal place or position. If “intrauterine device ectopic” is entered as a search term, no search results are obtained. If “intrauterine device” (which is a broad term for a concept in the diagnosis) is searched for and the results are filtered through the “disorder” semantic tag, 16 disorder-related terms are retrieved. Among them, the “malposition of intrauterine contraceptive device” concept is semantically equivalent to the “IUD ectopic” concept. In this process, the parent, child, and sibling concepts must be reviewed to confirm whether the concept is semantically correct, as mentioned above in the final process.Critically, to map semantically equivalent target SNOMED CT concepts, the mapping specialist must filter results by semantic tag in the SNOMED CT browser when entering a search term. These tags are presented in The mapping results can be classified according to the correlation between the source concepts and SNOMED CT concepts or according to map cardinality, depending on the number of concepts.According to the correlation, the mapping results can be classified as “1193548004 |Exact match between map source and map target (foundation metadata concept)|,” “1193549007 |Narrow map source to broad map target (foundation metadata concept)|,” or “1193551006 |Map source not mappable to map target (foundation metadata concept)|.” When the source term is matched to the equivalent SNOMED CT concept, the map is classified as a “1193548004 |Exact match between map source and map target (foundation metadata concept)|.” When the source term is matched to broader SNOMED CT concepts, the map is classified as a “1193549007 |Narrow map source to broad map target (foundation metadata concept)|.” When no concept broadly matches a source term, the map is classified as “1193551006 |Map source not mappable to map target (foundation metadata concept)|.”As an example, the source term “breast cancer, upper inner quadrant” in a diagnosis is equivalently matched to 373082000 , and the map is classified as “1193548004 |Exact match between map source and map target (foundation metadata concept)|.” Another example is that the source term “aortic valve stenosis occurred after mitral valve replacement” in the diagnosis has no equivalent SNOMED CT concept that can be equivalently mapped, so it can be mapped to the broadly matching “703223000 |Postprocedural aortic valve stenosis (disorder)|.” In this case, the map is classified as “1193549007 |Narrow map source to broad map target (foundation metadata concept)|.”If a single source code does not map to a single SNOMED CT concept, it is necessary to classify the map’s cardinality using a complex map. The mapping results can be classified as either “one to one” or “one to many” according to their cardinality. When a single source code is mapped to a single SNOMED CT concept, the map is classified as a “one to one.” When a single source code with broad or multiple meanings is mapped to multiple SNOMED CT concepts, it is classified as “one to many.” For example, the source term “right or left hemicolectomy” has 2 meanings: “right hemicolectomy” and “left hemicolectomy.” The source term is mapped to “359571009 |Right colectomy (procedure)|” and “82619000 |Left colectomy (procedure)|,” respectively, and the map is classified as “one to many.”The map is validated with internal and external validation. Internal validation may vary depending on how many individuals participated in the mapping and validation processes. When 2 mapping experts are involved, one maps the source terms and the other reviews the mapping results. Otherwise, both mapping experts could map the same source terms and then compare the maps constructed by each other. When more than 2 mapping experts are involved, a validation can be conducted by dividing them into 2 groups—mapping and reviewing groups. The map is deemed to be correct if the mappers and reviewers select the same results. If the maps differ, the results should be evaluated in a group discussion with the other mapper to agree on which SNOMED CT concept to use.External validation can also be used, in which clinical or mapping experts who were not involved in the mapping process verify the validity of the mapping results. Methods for performing external validation include reviewing the sample mapping results and obtaining mapping results that were difficult to map or that were not agreed upon in an internal group discussion.There are 2 types of maps—simple and complex maps. A simple map is a representation of mapping from a term in other code systems to a SNOMED CT concept; this is comprised of the source code , target SNOMED CT , and map correlation. A complex map is a representation of mapping from a term in other code systems to one or more SNOMED CT concepts; this is comprised of the source code , target SNOMED CT , map correlation, and cardinality. If map cardinality is 2 or more, rows are added to the final map. When documenting the final map, versions of source codes and SNOMED CTs, mapping dates, and mapper information must be included. A SNOMED CT mapping guideline has been developed for the terms used to document clinical findings and procedures in EMRs. It was developed based on a review of previous mapping guidelines and the literature and the experiences of the authors and the map guideline development committee members. During the development of this mapping guideline, we reflected on the methods of resolving the difficulties experienced in KCD-7 and EDI code mapping, such as preprocessing the source terms and selecting search terms. We also reflected on the methods and examples identified while teaching mapping specialists working in local institutions to map the terms used to document clinical findings and procedures in EMRs to the SNOMED CT at the Korea Human Resource Development Institute of South Korea since 2019 . The mapThe guidelines developed in this study contain detailed mapping steps from the Korean perspective, not only in the new steps such as term extraction, syntactic and semantic preprocessing, search term selection, and searching strategies in the SNOMED International browser but also in the steps adopted from previous mapping guidelines and studies ,27,38. FThis study had some limitations. Since the guideline focused on specific clinical domains, other clinical domains, such as medicine, were not included. Future studies are required on the development of mapping guidelines for terms used to document other clinical domains. In addition, this guideline does not include a guideline for mapping to SNOMED CT post-coordinated expression. The post-coordinated expressions frequently used in South Korea can be added as a new concept in the Korean extension of SNOMED CT.This study developed a SNOMED CT mapping guideline for the terms used to document clinical findings and procedures in EMRs at local institutions in South Korea. The guideline was based on existing mapping guidelines, the findings of previous studies, and the mapping and teaching experiences of the authors. The mapping guideline developed in this study consisted of the following nine steps: (1) define the purpose and scope of the map, (2) extract terms, (3) preprocess source terms, (4) preprocess source terms using clinical context, (5) select a search term, (6) use search strategies to find SNOMED CT concepts using a browser, (7) classify mapping correlations, (8) validate the map, and (9) build the final map format. The new guideline can be published on the website of the Korea Health Information Service. The guideline can be applied to local medical institutions when mapping Korean terms used to document clinical findings and procedures in EMRs to SNOMED CT. It will also support local medical institutions in standardizing their local code systems using SNOMED CT. Ultimately, the data quality of each local medical institution will be improved, allowing the data to be fully used in clinical decision support systems, health information exchange, and clinical research.


Music production is a universal phenomenon reaching far back into our past. Given its ubiquity, evolution theorists have postulated adaptive functions for music, such as strengthening in-group cohesion, intimidating enemies, or promoting child bonding. Here, we focus on a longstanding Darwinian hypothesis, suggesting that music production evolved as a vehicle to display an individual’s biological fitness in courtship competition, thus rendering musicality a sexually selected trait. We also extend this idea to visual artists. In our design, we employed different versions of naturalistic portraits that manipulated the presence or absence of visual cues suggesting that the person was an artist or a non-artist . Participants rated each portrayed person’s appeal on multiple scales, including attractiveness, interestingness, sympathy, and trustworthiness. Difference scores between portrait versions revealed the impact of the artistic/non-artistic visual cues. We thus tested Darwin’s hypothesis on both a within-subject and within-stimulus level. In addition to this implicit approach, we collected explicit ratings on the appeal of artists versus non-artists. The results demonstrate divergent findings for both types of data, with only the explicit statements corroborating Darwin’s hypothesis. We discuss this divergence in detail, along with the particular role of interestingness revealed by the implicit data. These artifacts show a stunning level of refinement and mastery, implying that the origins of music production and visual art must go back even way further into our past. This also holds true for art forms that do not depend on material objects, such as poetry, singing, or dancing, whose exact age is likely never to be determined3.Human engagement with the arts is present all around the globe and reaches far back into the prehistory of our species. Archeological findings date back to more than forty thousand years when it comes to musical instruments5. These practices are believed to have primarily served the purposes of attracting sexual partners and demonstrating social status, aligning with our modern behaviors such as wearing make-up, jewelry, brands, and insignia. A longstanding hypothesis in evolutionary psychology extends this logic to the production of music. The considerable efforts invested into acquiring a skill as time consuming and strenuous as music production suggests that musicality must have held adaptive value for individuals in prehistoric societies, particularly given the rough living conditions and obligations of that era.The first object our ancestors began to aesthetically modify were their own bodies, as suggested by archeological records of personal ornaments and ochre, a form of body paint, dating back at least 100.000 yearsThe Descent of Man6, Darwin proposes that human music production has its origins in sexual selection, specifically in courtship displays as they are used by many other species in order to signal genetic fitness and to impress the potential sexual partner. In Darwin’s own words: “musical notes and rhythm were first acquired by the male or female progenitors of mankind for the sake of charming the opposite sex” . Typical examples in the non-human realm include birds, apes, and whales, especially male representatives of the respective species11. For humans, Darwin’s hypothesis is standing to reason given the emotional power and impact music can exert on listeners14, along with the visually displayed mechanical skills involved in playing an instrument15. Together, this multisensory stimulus signals extraordinary motoric, cognitive, affective, and communicative capabilities of an individual, which might have remained hidden otherwise . The general tenet of Darwin’s idea was taken up and extended by a number of later theoreticians, particularly by Miller in the late 20th century18. It even came to prominence in the awareness of laypeople, as instructions on dating platforms such as Tinder imply, which (somewhat humorously) refer to using a profile image containing a musical instrument to increase one’s sex appeal  compared to the same profile without the guitar in the picture20. The cues systematically varied in terms of arousal and complexity. The results partially supported the sexual selection hypothesis, as the cues did increase the perceived attractiveness and dating desirability for both sexes. However, this overall effect was not moderated as expected by arousal and musical complexity.A recent study used cross-modal priming to test Darwin’s hypothesis. Participants were presented with short piano excerpts before viewing facial pictures, thereby establishing an associative link between the auditory cue and the visual target21 utilized verbal descriptions of fictitious profiles, systematically manipulating whether the described person was musically active  or not. The authors asked participants to rate the imagined attractiveness of the person described in the profile, as well as the motivation to engage with this person . The results did not comply with Darwin’s hypothesis; profiles containing verbal cues about music production did not increase their attractiveness. Instead, the results were more in line with the similarity-attracts hypothesis22, where musicians preferred musicians and non-musicians preferred non-musicians. One limitation of this study is once again the use of a between-subjects design and a small number of ratings per condition. Another drawback is the task itself. While attractiveness is largely based on visual processing, participants here had to provide attractiveness ratings based on textual material, which did not include any cues about the person’s visual appearance. Although not presenting a photograph and relying solely on imagination could be considered a potential strength of this design, it might also have made it more difficult for the effect to emerge.Another study23. Analyses of twin modelling in a large genetically informative sample revealed no significant relation between musical ability and mating success. However, it is worth noting (as discussed by the authors in the limitations section of their article) that most of the measures used in these analyses were not originally designed to test the sexual selection hypothesis. Instead, the authors had to use available variables from the sample and match them as closely as possible with the concepts relevant for Darwin’s prediction.Similarly, a study from the field of behavioral genetics found little support for Darwin’s idea25 could turn out to be premature, as the absence of evidence is not evidence of absence. Much more data are needed to confirm or refute Darwin’s idea. The current study aims to contribute a piece of evidence to the body of research and overcome some of the limitations of previous work.In sum, to date, only a handful of studies have dedicated their attention to testing the sexual selection hypothesis, presenting evidence both in favor and against Darwin’s idea. Additionally, most of these studies suffer from various limitations. Given this state of affairs, it is difficult to conclusively determine the validity of the sexual selection hypothesis. Thus, claims refuting the hypothesis based on missing evidence25. Some of these theories are not mutually exclusive with Darwin’s reasoning. In this study, however, we will exclusively focus on Darwin’s suggestion.It should be noted that Darwin’s line of thinking is not the only evolutionary approach to human musicality. Alternative accounts, for instance, emphasize the power of music to promote mother–child bonding, as in Ellen Dissanayake’s work, or facilitate social bonds in general. In contrast to focusing on in-group cohesion, some theorists bring into focus that music production can also be used for out-group exclusion, with martial music accompanying, for instance, war dances being typical examples for this function. Yet other theorists, most notably Steven Pinker, argue that musicality is a useless by-product of the evolution of the human central nervous system. A comprehensive overview and thorough discussion of alternative theoretical accounts on the evolution of musicality are presented inThe basic idea of the present study was to provide participants with two versions of a person’s photograph, similar to Tifferet et al., but in a within-subject setting. For this purpose, participants were invited to the lab twice, with a one-month gap between the sessions. One version of the photograph included cues related to the musical status of the depicted person, while the other version had no such cues. Consistent with with the sexual selection hypothesis, we anticipated that cues rendering a person a musician would boost their perceived attractiveness (Hypothesis 1a).26.While our primary focus was on music production, we also aimed to investigate the sexual selection hypothesis in relation to visual artists by incorporating portraits of painters and photographers (Hypothesis 1b). In general, we see no reason why other art forms could not have a similar enhancing effect on a person’s perceived attractiveness as music is believed to have, especially given that alongside musicality, aesthetic expression in the visual domain is among the oldest forms of our species. In fact, in his own writings, Darwin applied the same logic to other art forms, notably dancing and poetic languageOne could argue that adding any cues to a person’s portrait, which reveal their specific professional interests, might enhance their perceived attractiveness, regardless of their artistic status. For instance, providing cues that indicate a person is a teacher or a doctor could have a similar boosting effect on their perceived attractiveness. In his own writing, Darwin explicitly juxtaposes the human capacity for music production with more practical skills, which he refers to as “daily habits of life” ), that directly support an individual’s survival and wellbeing, as well as that of society on a large scale. Building on this notion, we aimed to compare musicians and visual artists with individuals specializing in non-artistic fields as a control group. We expected that, overall, the enhancing effect would be specific, or at least particularly pronounced, for musicians and visual artists, while being weaker or even absent for individuals with other specializations (Hypothesis 2). Translating the practical “habits of life” into modern terms, we included a wide range of portraits that provided cues about a person’s non-artistic vocational interests as part of the control group .27, Darwin himself did not propose a sexual dimorphism in musicality, where males would have superior abilities compared to females, as is often observed in the animal kingdom, such as in songbirds. In fact, Darwin even assumed the opposite: “Women are generally thought to possess sweeter voices than men, and as far as this serves as any guide, we may infer that they first acquired musical powers in order to attract the other sex.” .In accordance with Darwin’s line of thinking, we also anticipated that the enhancing effect would be strongest in cross-gender direction, while being weaker or even absent when participant viewed individuals of their own gender (Hypothesis 3a). It is worth noting that, in contrast to later authors28; for music, see29).Finally, to consider the possibility of ceiling effects, we anticipated that the enhancing effect would be most pronounced for faces with average or lower attractiveness (Hypothesis 3b). In other words, for individuals with highly attractive faces, adding attributes related to their artistic status would not have a measurable incremental effect. In a related vein, recent studies on mate choice have demonstrated that lower facial attractiveness can be compensated for by an individual’s aesthetic creativity :Finally, we also obtained an implicit measure of how much time participants spent viewing each portrait before switching the screen (via a button press) to submit their ratings . To summarize, we formulated five a priori hypotheses and preregistered them on the Open Science Framework  that participants had to provide in each session. In addition to this implicit approach, we were also interested in whether participants explicitly considered artistic individuals to be more attractive  than non-artistic people. We collected these explicit ratings at the very end of the second session .In the first step, we collected a large pool of almost a thousand high quality, half-length portraits from the internet, featuring musicians, visual artists, and various non-artistic vocational categories. We sourced these stimuli from actual images found on personal and commercial websites, the press, as well as stock photography. The half-length (or torso) portraits depicted individuals in everyday settings, providing cues about their artistic status or their other specialization. For instance, in the case of musicians, the portraits showed individuals sitting at a piano, harp, or drum set, or holding musical instruments such as a flute, an e-guitar, or a microphone (for singers). We made sure to represent a wide spectrum of instruments and musical styles, including classical, rock, pop, and electronic music Table .Table 1NIn the second step, we systematically reduced the number of stimuli. Particular attention was given to balancing genders within and across all categories and subcategories, as well as their level of attractiveness. Our goal was to provide a diverse range of physical facial attractiveness while avoiding any systematic differences between artists and non-artists. This pre-selection process was based on judgments from a select group of highly experienced raters within our lab. However, the data collected from the actual sample validate our pre-selection, as discussed later in the manuscript  were invited to the lab for a study titled ‘Faces in Everyday Life,’ as stated in the announcement. Participants were recruited through advertising on the university campus and from our institute’s internal participant database, which includes a substantial proportion of individuals who are not students. This contributed to the aforementioned mean age of 33 years. All participants provided informed consent and were compensated with either 40 Euros or course credit after the second session of the experiment. All participants had normal or corrected-to-normal vision and none was excluded from the analysis. The manuscript does not contain any information that could lead to the identification of a study participant.Eighty German-speaking participants .Presentation®22.1 , including a custom-made open-source user interfaceThe ratings for the target concepts of Attractiveness, Interestingness, Sympathy, Trustworthiness, and Wish-to-Meet were assessed using a movable cursor on bipolar scales ranging from  − 10 to + 10. The poles of the scales were verbally anchored with adjective antonyms: ‘unattractive, attractive’, ‘unlikable, likeable’, ‘uninteresting, interesting’, and ‘untrustworthy, trustworthy’. The question above the scales read: ‘To what degree do you experience the depicted person as…?’. The participants’ task was to position the cursor at the appropriate point, and we recorded their responses with a finer resolution than presented to them, specifically within a range between  − 50 and + 50. The motivation to meet the depicted person was measured using a similar scale, but on a separate screen see Fig. . The quePlease note that, although we are aware that the mechanism of sexual selection, as described by Darwin, ultimately focuses on sexual contact, we refrained from directly asking how much participants would like to have sex with the depicted person. This wording was perceived as inappropriate in pilot sessions, particularly by participants above 30 years of age. However, we are convinced that asking about ‘feelings of attractiveness’ effectively captures the judgment we intended to measure, as in German, the semantics of ‘attraktiv’ carry a strong connotation of romantic attraction. Since our participants were German native speakers, we can rule out the possibility that they misinterpreted the target concept as Platonic interest in another person. Furthermore, informal conversations we had with the participants after the second session confirmed our assumption that they understood the ratings as we intended.In each session, participants were presented with a total of 190 portraits. The order of the stimuli within each session was randomized for each participant. Additionally, we prepared two versions of the experiment to counterbalance whether a person’s torso or face was presented in the first session. Each session lasted approximately 60 min per participant, with self-paced breaks available during the session.Sociodemographic information, which encompassed participants’ own musical and artistic statusParticipants’ self-perceived own attractiveness, sympathy, interestingness, and trustworthinessParticipants’ personal preferences regarding the professions they encountered in the studyA section for participants to report any observations or comments they wished to communicateThe second session occurred at least three weeks after the first one, with an average time gap between sessions of 27.6 days, and it followed a similar structure. However, at the conclusion of the second session, we collected additional data consisting of:Data from (a) to (c) were collected for potential use as covariates in subsequent analyses, while (d) aimed to determine whether participants noticed that each face appeared twice during the testing; eight participants, constituting 10% of the sample, reported to have noticed this. As a final step, we asked participants to explicitly compare artistic individuals with non-artistic individuals using 7-point bipolar Likert scales. These scales included ‘unattractive, attractive’, ‘unlikeable, likeable’, ‘uninteresting, interesting’, ‘untrustworthy, trustworthy’, ‘uneducated, educated’, ‘incompetent, competent’, ‘distanced, empathic’, ‘unsociable, sociable’, ‘boring, exciting’, ‘unintelligent, intelligent’, and ‘unreasonable, reasonable’. The statement preceding the scales read: ‘Artistic people  are compared to non-artistic people more…’ The verbal anchors along the scales were ‘very much’ (positioned at 3), ‘considerably’ (positioned at 2), ‘somewhat’ (positioned at 1), and ‘similar’ .The study was conducted in accordance with the Declaration of Helsinki. All methods and procedures were approved by the Ethics Committee of the Max Planck Society .−4 s, were log-transformed to remove the skewness of the original data.The study followed a 2-by-3 factorial design, with the portrait’s Layout  and the Status of the depicted person  as factors manipulated within each participant. We also included the gender of both the participants and the depicted individuals  as moderating factors to test Hypothesis 3a. Similarly, we included the mean rating for each facial portrait  as a moderating covariate to examine Hypothesis 3b . No centering of predictors was performed since they resemble categorical factors, except for the portraits’ mean ratings, which were centered around the grand mean prior to fitting the models. Additionally, the time durations of portrait viewing before submitting the ratings, measured by Presentation in 1033 using the lme4 package version 1.1–2734. Restricted maximum likelihood (REML) estimation method was applied to obtain the parameter estimates. P-values were obtained using the lmerTest package35. Following a recent review’s recommendation36, we also report the profile likelihood confidence intervals (PLCI) with 95% boundaries (in square brackets following each parameter). These intervals were computed using the confint function within the lme4 package. Effect sizes are reported as d measures following Westfall et al.37’s recommendation, calculated as the estimate for fixed effect divided by the square root of the pooled variance of random effects.As preregistered, we employed linear multi-level modeling (LMM) to investigate our hypotheses since the data exhibit a nested structure, with portraits at Level 1 and participants at Level 2. All statistical analyses were conducted in R38, using the emmeans package version 1.7.239. Post-processing of figures was carried out using Adobe Illustrator.All data and analysis scripts, including models and code necessary to replicate the figures and tables, are available on the Open Science Framework. To visualize the results, we computed estimated marginal means (EMMs), which include 95% confidence intervals as error barsWhen participants were asked at the end of the study to explicitly compare artistic and non-artistic individuals, they favored the artists on almost all scales, except for Trustworthiness and Reason. Particularly notable was their positive judgment regarding Interestingness Fig. .Figure 3ß = 0.001 , t = 2.657, p = 0.009, d = 0.002; torsos: ß = 0.001 , t = 2.164, p = 0.032, d = 0.002; for statistical details, refer to Supplementary Table Before delving into the results of our main hypotheses, we would like to report on two general findings. First, the results of an LMM predicting viewing times based on the mean facial attractiveness indicate that more attractive faces were associated with longer self-paced viewing times for both layout formats , in which we allowed intercepts to vary between participants and stimuli:ß = 3.327 , t = 14.110, p < 0.00001, d = 0.159), which is the contextual enhancement effect we already know from the General Observations. Second, a significant interaction between Layout and Status, reflecting that musicians have a lower boost than both non-artists  and visual artists . This interaction is of main interest for our hypothesis, as it indicates a moderating quality of the person’s artistic status on the strength of the contextual enhancement effect .The results show two significant effects .To directly compare the boosting effect among the three status groups , we conducted a second analysis in which the boost was predicted directly by the person’s status (Model-A-Boost). This model is identical to Model-A, with the exception that the factor Layout is dropped, as the difference between the layouts is expressed directly in the dependent variable Boost. This approach is stricter for testing the hypothesis due to the smaller variance in our difference scores when compared to the original values , which is driven by the musicians’ lower boost when compared to non-artists .The results of Model-A-Boost , whereas neither of the two additional gender factors nor their interaction term had any power to predict the boost effects  nor its interaction with Status  can predict the attractiveness boosts  and the Status factor. The results show that neither mean facial attractiveness  as well as the self-paced Viewing Time. Detailed results of these H2 analyses, along with the figures equivalent to Fig. Assumed age of the portrayed character. For this, ten independent raters  who were not part of the original sample estimated the person’s age on each portrait, and we averaged these ratings per stimulus.Gender of the portrayed character.40).Smile intensity of the portrayed character. We used intensity estimates of Action Unit 12  from the Facial Action Coding System .On the side of the raters, we controlled for:ß = −0.402 , t = −4.317, p < 0.0001, d = 0.02) and Wish-to-Meet . Conversely, personal preference for specific professions has a positive influence on all rating scales . Moreover, when comparing the models, it is evident that including the covariates significantly improves the statistical model fit, except for adding the gaze direction of the portrayed character, the rater’s own gender, and their own musical status  or when considering the mean facial attractiveness of the portrayed character. Importantly, artists and non-artists did not differ on any of the scales used in our study, meaning that Status alone had no predictive power for any rating scale as a main effect  than non-artists, participants decided in favor of the artists on almost all scales Fig. . AdditioThe discrepancy between the implicit outcomes and the conscious judgments is a puzzling inconsistency! It may reveal a general disparity in people’s explicitly stated attitudes towards artists compared to their unconscious dispositions. In other words, only the explicit (and publicly expressed) view of artists is highly appreciative. This aligns not only with Darwin’s reasoning but also with (Western) social conventions, which attribute high personal and societal value to the arts and those who practice them. Explicit reports can thus be subject to distortions by social desirability. On an implicit, unconscious level, however, our data suggest that musicians and visual artists are perceived as less attractive, less likeable, and also less reliable than non-artists.The only exception is Interestingness for visual artists, which was the only outcome consistent with the sexual selection hypothesis Fig. . While w43 on our boost data, which we grand-mean-centered for this purpose . First, we predicted Wish-to-Meet by Attractiveness . Unsurprisingly, this resulted in a positive association . Next, we tested the link between Attractiveness and Interestingness (path a between the independent variable and the moderator). This also showed a significant effect: ß = 0.516 , t = 20.92, p < 0.001, d = 0.026. In the last step, we predicted the effect of the mediator Interestingness on the dependent variable Wish-to-Meet , as well as the effect of Attractiveness on Wish-to-Meet when controlling for the mediator Interestingness . The decrease in the effect of path c to path c’  indicates that the link between Attractiveness and Wish-to-Meet is partially mediated by Interestingness. In other words, the desire to meet a depicted person is influenced to a substantial degree by attractiveness that is based on the interestingness this person radiates. Interestingness in turn is particularly pronounced for people who are artists, especially visual artists, as our data suggest , we observe that the contextual enhancement effect can be overridden by the raters’ general reluctance to a particular professional group. Here, half-length portraits received equal, and by tendency even lower, scores than facial portraits. The approach of cropping information on a person’s profession, interests, and surrounding environment could thus be useful in research contexts other than mate choice.In conclusion, it is important to note that in this study, we tested Darwin’s hypothesis using a Western sample. It would be important to adapt and replicate our design with samples from other cultural backgrounds. Additionally, while we chose to use an implicit approach in this study, research designs that incorporate controlled use of confederates are particularly valuable. They would come closest to what Darwin had in mind when formulating his idea—an authentic multi-sensory real-life interaction between individuals. To our knowledge, studies of this nature have never been conducted. However, based on our current findings, we strongly encourage such future studies to include valid control conditions and not rely solely on explicit judgments.29). Superior performance, in fact, is essential to the general mechanism of sexual selection. Only individuals with exceptional performative abilities  are likely to have the best chances of passing on their genes, thereby perpetuating the genetic basis of the very characteristics that enabled their exceptional performance in the first place. For musical displays, we would expect the effect to emerge more prominently in the case of highly skilled virtuosic musicians performing in front of an enthusiastic and admiring audience. Such scenarios are also likely to result in a perceivable boost in the person’s social standing. Conversely, poor performances that lead to reactions of embarrassment and disdain from the audience would likely have the opposite effect. In other words, we would not expect a positive effect from just any form of music making. The aspect of skill level was not the focus of our study. However, this applies to all specialization, including the non-artistic controls , which can also systematically vary in terms of skill level. Since higher skill levels are likely to be preferred by participants in general, it will remain important for future studies to investigate the specificity of this variable’s impact on romantic attraction by separately examining artists and non-artists.Future research could also systematically manipulate the level of performative skill of an artist or musician, as the effect described by Darwin might be bound to outstanding display behavior (early results do suggest this directionIn addition to considering the skill level, future studies should also take into account the emotional impact on the perceiver. In his writings, Darwin emphasizes repeatedly the emotional power and seductiveness of music. The emotional impact might be another necessary component for the mechanism to be triggered.Supplementary Information.


This study examines adjective-noun order in code-switched constructions by heritage speakers of Spanish and Papiamento in the Netherlands. Given that Dutch differs from Spanish and Papiamento regarding the default position of the adjective, word order in the nominal domain creates a so-called “conflict site” in code-switching. Most accounts of word order patterns in code-switching focus on structural constraints, such as the matrix language or the strength of the EPP feature in Agr. Thus far, studies comparing the two models have not found compelling evidence for either of them.The present study takes a more comprehensive approach and considers several linguistic  as well as extra-linguistic variables . Moreover, we compare heritage speakers of two different heritage languages that are linguistically similar , and share the same dominant societal language, but are likely to differ from each other in terms of certain sociolinguistic properties. 21 Spanish and 15 Papiamento heritage speakers (aged 7–54) in the Netherlands carried out a Director-Matcher task, aimed at eliciting nominal constructions containing switches.The results show that either the ML or the language of the adjective, or both, are important predictors for word order, although the data cannot disentangle these two factors. Moreover, the type of insertion was found to play a role: word order patterns for noun insertions differed from other types of insertions. In addition, the two groups did not behave similarly: Papiamento speakers were more categorical in their preference for noun-adjective order when inserting Dutch nouns into their heritage language than the Spanish speakers were. Finally, there was a great deal of individual variation, which seemed to be related mostly to the age of the participants: children and teen participants behaved differently from adults.These findings demonstrate that both linguistic and extra-linguistic play a role in determining how heritage speakers deal with conflict sites in the nominal domain. Particularly, the findings suggest that, at least for some communities and in some code-switching modes, children may need more time, or more input, too converge on adult-like code-switching norms. This phenomenon is known as code-switching CS; . In studcf.cf. section 2). Hence, Spanish-Dutch and Papiamento-Dutch code-switching between the noun and the adjective could result in four potential noun-adjective combinations , so the question that arises is whether they are all possible or whether some combinations are disallowed in the bilingual grammars of these speakers. Due to the generally low occurrence of attributive adjectives in production data  as well as age of onset and patterns of use and exposure, in order to investigate which, if any, of these factors play a role in determining code-switching patterns. We focus on heritage speakers of Spanish and Papiamento who live in the Netherlands, targeting switching where the structures of the two languages differ lexified by Spanish  spoken iAccording to data from the Central Bureau of Statistics (CBS) in 2019, a total of 130,160 people living in the Netherlands come from Spanish-speaking countries. About a third of the Spanish-speaking population comes from Spain, and many of these migrated to the Netherlands in the 1960 and 1970s as contracted workers. The rest came from a range of Spanish speaking countries in Latin America, where dictatorships and civil wars caused a wave of political refugees during the 1970 and 1980s. More Spanish-speaking people migrated to the Netherlands during the 1990s  een zwarte hamer a black hammer “a black hammer”Spanish(2) un martillo negro a hammer black “a black hammer”Papiamento(3) un martin pretu a hammer black “a black hammer”In Spanish, the placement of a number of adjectives with respect to the noun varies depending on the semantic interpretation of the adjective, see examples in (4a) and (4b). Certain adjectives tend to be placed before the noun, such as gran (great) and buen (good), or can only appear before the noun, such as mero (mere). Most adjectives however tend to be placed after the noun, and some are strictly ungrammatical in prenominal position, such as adjectives which indicate nationalities or—important to this study—colors (2).(4) a.un hombre pobre a man poor “a poor (poverty-stricken) man”  b. un pobre hombre a poor man “a poor (piteous) man”Papiamento adjectives behave similarly to Spanish ones, and may appear prenominally, which then changes its meaning , “encodi(5)  a. homber pober man poor “poor (poverty-stricken) man”  b. pober homber poor man “poor (piteous) man” , p. 162The stimuli for the current study, however, were designed to elicit color adjectives, which leave no room for interpretation and are always postnominal in both Spanish and Papiamento, and prenominal in Dutch.3.3.1.According to the Matrix Language Framework MLF, , 2002, tAnother approach, which is grounded in the Minimalist Program (MP), assumes that the features of the lexical items should account for CS/bilingual grammars . Thus, ccf.Several studies have tried to differentiate between these two models, but no clear conclusion can be drawn  determine word order preferences?What is the role of extralinguistic factors, both at the individual level and at the community level, in accounting for heritage speakers’ preferences in code-switched speech?5.5.1.n = 12), teenagers , and adults (n = 17). The Spanish-speaking participants had backgrounds from a range of Spanish speaking countries, such as Argentina, Colombia, Ecuador, Mexico, Paraguay, Peru, and Spain among others. The Papiamento heritage speakers all came from or have a family background in Curaçao and Aruba. The background questionnaire contained several questions about the participants’ patterns of use and exposure to both languages. They were asked to report their usage of Dutch and of the HL, both with immediate family and non-immediate family, the number of hours per week they received other input  in their HL, the frequency with which they visited their country of origin [on a scale from 1 (never) to 4 (once or multiple times a year)], their self-reported skill in their HL , and whether they had received any official classes/courses in their heritage language while living in the Netherlands. The questionnaire for the children also contained questions about current input and input in their heritage language at age 0–4. This information is summarized in A total of 36 heritage speakers living in the Netherlands participated in this study. We would like to note that we use the term heritage speaker, even though not all participants are considered as such under all definitions, for example because they arrived in the Netherlands well after the onset of school. However, given that age of onset was one of our variables of interest, it was considered important that our sample included a wide range of ages of onset. Of the 21 Spanish heritage speakers, 11 participants were born in the Netherlands (two of whom spent a few years of their lives in another Spanish-speaking country later in childhood), four arrived in the Netherlands before starting their primary education, and the remaining six arrived in the Netherlands between the ages of 6 and 12. Of the 15 Papiamento heritage speakers, three were born in the Netherlands, two arrived before going to primary school, and the remaining 10 arrived when they were between 6 and 21 years old. However, it must be noted that all Papiamento-speaking participants were exposed to Dutch to a certain extent before arriving in the Netherlands, given that Dutch is an official language in Aruba and Curaçao, where all participants were from. As mentioned, our participants varied considerably regarding their ages at testing (8–54). The participants can be divided into three age groups: children  and (7)], in order to check whether the participants were able to use the target word order in each of their languages. Immediately after the unilingual modes, they carried out the same task in two different code-switching modes. First, they were instructed to complete the task in their HL again, but this time they were asked to name just the object in Dutch (8). Finally, the participants were instructed to use Dutch, and name the object in the heritage language (9). This order was chosen for two reasons. Based on the assumption that our participants were not likely to highly frequent code-switchers, we considered that it would be easier for them to understand the task if they started with the unilingual mode. Moreover, maintaining the same order for every participant allowed us to analyze observed differences between groups without having to take into account any potential effect of order.(6) Arriba de la casa roja está el libro blanco Above de house red is the book white “Above the red house is the white book”(7) Naast de zwarte kam ligt de groene hoed Next to the black comb is the green hat “Next to the black comb is the green hat”A la derecha de labloemblanca está elboekverde(8)  To the right of the flower white is the book green “To the right of the white flower is the green book”Onder het zwartecasa is de rodeflor(9)  Underneath the black house is the red flower “Underneath the black house is the red flower”At the beginning of the procedure, the participants were asked in which language they would like to receive instructions, the questionnaire, and consent forms, in Dutch or in their heritage language. The participants (or their parents in the case of child participants) first signed a consent form. After this, they completed the task while being given precise instructions. Only after they had completed the first round of the task in the heritage language were they told to do the next round in Dutch, and so on. After having completed all four rounds of the task, the participants (and/or parents) were asked to fill out the background questionnaire.6.n = 39) or where the adjective was part of a relative clause construction  were excluded.In the analysis presented below, we only included those instances where an adjective was produced either directly preceding or following the noun. Those cases that lacked an adjective . In 99% of these cases, the languages of the verb or these other elements coincided with the language of the experimental mode. Based on this information, it was considered safe to assume that the language of the verb and/or other elements in the sentence could be used as an indicator for the matrix language.In this section, we ask to what extent this variability can be explained by linguistic factors. In this part of the analysis, we collapse the data for the two heritage groups, given that Spanish and Papiamento behave similarly when it comes to word order in the nominal domain. In the introduction, two linguistic variables were mentioned that have been proposed to account for word order constraints in code-switching: the matrix language and the language of the adjective. While identifying the language of the adjective is straight-forward, the same is not true when it comes to determining the matrix language. Even though the participants were instructed to speak one language and embed nouns from the other language, it is not guaranteed that they in fact consistently follow these instructions. A potential solution to this problem is to determine the matrix language for each clause based on the language of the verb cf.. Howeveronly noun phrases were excluded, leaving us with 1,574 instances. A total of 711 instances that consisted of only the object in the other language. This led to a high number of noun insertions .What immediately becomes clear from this table, is that the matrix language almost always coincides with the language of the adjective . This could be due to the nature of our task: participants were explicitly instructed to name n = 36) and other times language of the adjective (n = 22). These data thus suggest that either the matrix language or the language of the adjective, or both, seem to play a role in determining word order in code-switched productions. However, the data cannot help us disentangle between these two factors. Moreover, even when both the matrix language and the language of the adjective align, there is still variation, which suggests there may be other factors playing a role.When the matrix language and the adjective were Dutch, adjective-noun (the Dutch word order) was used more often (607 out of 759 cases), whereas when the matrix language and the adjective were Spanish/Papiamento, noun-adjective (the Spanish/Papiamento word order) was preferred (712 out of 750 cases). For the few cases where the language of the adjective did not coincide with the matrix language , we see a general preference for noun-adjective word order, which sometimes aligned with the matrix language , there were also 66 determiner-noun insertions (example 11), 18 adjective insertions (example 12), 30 noun + adjective insertions (example 13), and 18 det + noun + adjective insertions (example 14).Elkamnegro está arriba” (10) “ The comb black is above “The black comb is above”Después esde bloemnegro”(11) “ Next is the flower black “Next is the black flower”en een bloemblanku”(12) “… and a flower white “… and a white flower”met daaronder eenkama pretu”(13) “… With underneath a bed black “…with underneath a black bed”Daarnaun llave rojo”(14) “ after that a key red “After that, a red key”What becomes clear from To see whether any of these effects was statistically significant, we ran a series of linear mixed effects regression models, using the lme4 package in R . The depz = 2.97, p = 0.003), insertion type , and the interaction between these two variables , which confirmed the observation that the word order is determined by the Matrix language in the case of noun insertions, but not for all other types of insertions, in which case noun-adjective is the preferred word order overall .We performed two analyses, one on the Dutch mode for both groups, and one on the HL mode for the Spanish group only, given that there was close to zero variation in the Papiamento group in this mode. For the analysis on the Dutch ML experimental mode, the dependent variable was word order (adjective-noun vs. noun-adjective). We considered the following predictor variables: heritage community, age at testing, age of onset of the societal language, length of residence in the Netherlands, use of Dutch with immediate family, use of Dutch with non-immediate family, total use of Dutch, average “other” exposure to the HL , whether or not they had had any instruction in their HL, and self-rated proficiency in their HL. Heritage community was a binary variable with two levels: Spanish and Papiamento. Similarly, instruction in the HL was a binary variable with two levels: yes and no. For these two binary variables, sum-coding was used. Age at testing was a categorical variable with three levels , for which orthogonal sum-to-zero coding was used such that contrast 1 compared teens and children (+1/3 for both) to adults (−2/3) and contrast 2 compared teens (+0.5) to children (−0.5). The remaining predictors of interest were continuous variables which were centered and standardized.Some of these variables are inherently related. For instance, age at testing, age of onset of the societal language, and length of residence are all derived from one another. To avoid multicollinearity issues, we first checked for each of them to what extent they improved the model fit compared to a null model which just included a random intercept for subject. The variable that explained most variability was age at testing. In a similar way, it was decided to include both usage of Dutch with immediate family and with non-immediate family, but not total usage of Dutch.VIF) for the final model, and eliminated several variables based on this information. The final model , heritage community , as well as a significant interaction between these two , which indicated for the Papiamento HSs, younger participants use noun-adjective order relatively more when they insert HL nouns into Dutch, whereas for the Spanish HSs, this is not the case . For the independent variables, the following were considered: age at testing, age of onset of the societal language, length of residence in the Netherlands, usage of Spanish with the immediate family, usage of Spanish with non-immediate family, total usage of Spanish, exposure to “other” exposure to Spanish , self-rated proficiency in Spanish, and whether or not they had received instruction in Spanish. Similar to the model for the Dutch experimental mode, instruction in the HL was a binary variable which was sum-coded, age at testing was a ternary variable for which orthogonal sum-to-zero coding was applied as described above, and all other variables were continuous and were centered and standardized.z = 2.02, p = 0.04), as well as a significant intercept for subject. The effect of age indicates that younger participants use the adjective-noun orders relatively more when they insert Dutch nouns into Spanish  and Spanish or Papiamento . We observed that word order in these cases is constrained both by linguistic factors and by non-linguistic factors.cf.cf.Concerning linguistic factors, similar to previous studies  we foundLet us start with the second most frequently produced type of insertion after noun insertions: determiner-noun insertions, illustrated in example 15 for Spanish with a Dutch insertion (repeated here) and 16 for Dutch with a Papiamento insertion.Después es debloemnegro”(15) “ Next is the flower black “Next is the black flower”Onder die rooiekas, un kurasonwit”(16) “ Below that red house a heart white “Below that red house, a white heart”This type of insertion occurred 66 out of 1,574 times in our data (37 times for Dutch as the ML and 29 times for Spanish/Papiamento as the ML) and in all cases, the adjective followed the noun. Note that the second example contradicts both the predictions from the MLF and the MP. We would like to suggest the preference for the postnominal adjective in these cases may be explained from the perspective of processing economy. If the adjective would precede the noun, the speaker would have to switch back and forth between languages several times: the verb in the ML, the determiner in the inserted language, then the adjective in the inserted language and the noun in the ML again, which may not be the most economic strategy.In addition to these determiner-noun insertions, there are some insertion types that seem to be used as specific strategies by individual speakers. For instance, one Spanish heritage speaker uses almost exclusively Dutch (det-)noun-adjective insertions, always with a postnominal adjective, as in example 17:Arriba delhartje withay unsleutel groen”(17) “ Above the heart white there is a key green “Above the white heart there is green key”The same individual variation was found in other insertion types as well. For instance, postnominal adjectives with noun insertions into Dutch were dispreferred by most participants, but for some speakers this was actually the preferred option. This indicates that different participants seem to adhere to different strategies.In part, these different strategies were related to the specific linguistic communities. For instance, Papiamento speakers of all age groups categorically produced postnominal adjectives when the ML was Papiamento, whereas the Spanish speaking participants showed variation in the same context. However, this variation mostly pertained to the younger participants; the adult Spanish speakers almost categorically preferred noun-adjective order, similarly to the Papiamento speakers. Interestingly, the reversed pattern was observed when Dutch was the matrix language: here, an age effect was observed for the Papiamento speakers, but not the Spanish speakers. While Papiamento speaking children preferred noun-adjective word order, the adults almost categorically produced prenominal adjectives. This difference between children and adults is in line with studies by The difference between the Papiamento and the Spanish speakers in our study is most likely not related to linguistic differences between Papiamento and Spanish, given that the two languages overlap in terms of word order in the nominal domain. However, there are important sociolinguistic and sociohistorical differences between these communities that may explain their differential behavior. First, the Papiamento community in the Netherlands is bigger and more established, compared to the migrant Spanish community, in part because it has a longer history of post-colonial relationship. This may mean there is more contact between the members of the Papiamento community than between Spanish-speaking immigrants and their descendents. Second, all Papiamento HSs, even those who were born in Aruba or Curaçao had knowledge of Dutch before migration given the official stats of Dutch, contrary to Spanish HSs who were born in Spanish-speaking countries. Therefore, it is possible that language mixing is more common in the Papiamento community, and that for this reason there are clearer community norms than for our Spanish-speaking participants. In fact, we know from previous research  that PapThe Spanish-speaking differs from the Papiamento-speaking group in several ways. First of all, while the adult participants categorically prefer noun-adjective order when Spanish is the ML, similar to the Papiamento speakers, Spanish-speaking children and teens show more variability in this direction than their Papiamento-speaking counterparts. It may be the case that these speakers are less accustomed to code-switching in general, and as a result of this, children need more time and exposure to code-switching in the input to converge on the adult norm. The two groups also differ in the other code-switching direction: Dutch as the ML with HL words inserted. While the Papiamento speakers categorically choose adjective-noun order in this direction, all Spanish-speaking age groups, including the adults, show a considerable degree of variation. The increased variability in this code-switching direction may indicate that they are less accustomed to this direction, and therefore no clear-cut norms have been established. Given that we do not have information on the code-switching habits for our Spanish-speaking participants, these explanations remain rather speculative and need to be substantiated by further research.cf.In sum, our data suggest that word order variation in code-switched constructions in the nominal domain is determined by various factors, both linguistic ones  and extra-linguistic ones (community and age group). Therefore, the field needs to broaden its focus and take into account all the different variables that may play a role, either by careful controlling of the materials and/or the participants, or by including many variables as potential predictors, which is the approach taken in this study. We contend that, while theories such as the MLF or the MP have been essential in our understanding of code-switching, we also need to acknowledge that any theory that focuses on purely grammatical factors probably cannot be considered an accurate reflection of what happens in reality. As our study, as well as other recent studies cf. demonstrFinally, we need to acknowledge that our study has some limitations that may have affected our results. Given that adjectives do not occur often in spontaneous speech , and eveAnother issue to consider includes priming whereby one speaker’s code-switching facilitates another speaker’s similar switching . A recenThe research outlined in the present study constitutes an attempt to keep widening the research perimeter on code-switching. Our (so far preliminary) findings call for further research to be able to establish the theoretical and empirical implications of our findings. Only after studying different and similar language combinations in different contact situations will we be able to arrive at a description of the different dimensions that characterize code-switching and unveil the factors that modulate bilingual grammars.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.The studies involving human participants were reviewed and approved by Complying with the Ethics Code for linguistic research at the Faculty of Humanities at Leiden University, for this study written informed consent from all participants (including the parents/guardians of the child participants) was obtained prior to their participation. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.BO: data curation, statistical analysis, and writing. BS and IB: methodology, data collection, data transcription and coding, and writing. MP: conceptualization, methodology, writing, and funding acquisition. All authors contributed to the article and approved the submitted version.https://www.student.universiteitleiden.nl/en/vr/humanities/research-traineeship?cf=humanities&cd=latin-american-studies-ma).BO acknowledges that this work has received support by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 101024053. MP acknowledges support from the María Zembrano program  and the Traineeship in the Humanities Program at Leiden University (The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Policy is receiving increasing attention in the field of implementation science. However, there remains a lack of clear, concise guidance about how policy can be conceptualized in implementation science research. Building on Curran’s article “Implementation science made too simple”—which defines “the thing” as the intervention, practice, or innovation in need of implementation support—we offer a typology of four very basic ways to conceptualize policy in implementation science research. We provide examples of studies that have conceptualized policy in these different ways and connect aspects of the typology to established frameworks in the field. The typology simplifies and refines related typologies in the field.Four very basic ways to think about policy in implementation science research.1) Policy as something to adopt: an evidence-supported policy proposal is conceptualized as “the thing” and the goal of research is to understand how policymaking processes can be modified to increase adoption, and thus reach, of the evidence-supported policy. Policy-focused dissemination research is well-suited to achieve this goal.2) Policy as something to implement: a policy, evidence-supported or not, is conceptualized as “the thing” and the goal of research is to generate knowledge about how policy rollout (or policy de-implementation) can be optimized to maximize benefits for population health and health equity. Policy-focused implementation research is well-suited to achieve this goal.3) Policy as context to understand: an evidence-supported intervention is “the thing” and policies are conceptualized as a fixed determinant of implementation outcomes. The goal of research is to understand the mechanisms through which policies affect implementation of the evidence-supported intervention.4) Policy as strategy to use: an evidence-supported intervention is “the thing” and policy is conceptualized as a strategy to affect implementation outcomes. The goal of research is to understand, and ideally test, how policy strategies affect implementation outcomes related to the evidence-supported intervention.Policy can be conceptualized in multiple, non-mutually exclusive ways in implementation science. Clear conceptualizations of these distinctions are important to advancing the field of policy-focused implementation science and promoting the integration of policy into the field more broadly. Contributions to the literatureThis Debate article aims to provide clear, concise guidance about how policy can be conceptualized in implementation science research.A typology of four ways of thinking about policy in the field is presented: (1) policy as something to adopt, (2) policy as something to implement, (3) policy as context to understand, and (4) policy as strategy to use.Examples are provided of studies that have conceptualized policy in these different ways.The article consolidates and simplifies previously published typologies and frameworks that are relevant to policy-focused implementation science.Policy is receiving increasing attention in the field of implementation science –12. AlthDespite growing enthusiasm for policy-focused work in implementation science, conceptualizing policy questions in the field often feels like the proverbial problem of hammering a square peg into a round hole. This is in part because implementation science emerged from the evidence-based medicine movement . As a revery basic ways that policy can conceptualized in implementation science. We hope that our simplified typology will provide clear, concrete, and concise guidance to help implementation scientists conceptualize and conduct policy-focused research. Furthermore, we hope that it will support the integration of policy into implementation science research that is focused on clinical, organizational, and community settings. The guidance offered here simplifies and refines related typologies in the field [This concise Debate article aims to help implementation science researchers address this mismatch. Inspired by Geoff Curran’s article “Implementation science made too simple,”  the artihe field , 21–24.policymaking, policies (codified in statutes and rules), and policy implementation. Across these domains, it is imperative to specify whether the policy of focus is public  or private  [Figure licies”) . For publicies”) . Furtherlicies”)  of an inHere, a specific policy proposal is the focus of the research question and conceptualized as “the thing” per Curran’s terminology   is disseminated to policymakers –31, survHere, a specific policy is also the focus and conceptualized as “the thing.” The policy of focus does not need to be evidence-supported, however, as policies without an evidence base are frequently implemented in the real world. The extent to which these policies produce benefits or harms to public health, and ameliorate or exacerbate health inequities, can often hinge upon implementation processes. When conceptualizing policy in this way, the goal is to generate knowledge about how the rollout of polices can be optimized to maximize benefits for population health and health equity.Policy-focused implementation research is well-suited to achieve this goal and has a long history in the field of public administration research . ExampleHere, an evidence-supported clinical, organizational, or community intervention is “the thing,” and policy is conceptualized as a fixed determinant of implementation outcomes. The goal, when conceptualizing policy this way, is to understand the mechanisms through which policies affect implementation of the intervention, and how clinically, organizationally, or community-targeted implementation strategies might be selected and tailored for different policy contexts . AlthougHere, an evidence-supported clinical, organizational, or community intervention is “the thing,” and policy (either “big P policy” or “little P policy”) is conceptualized as a strategy to affect implementation outcomes. When conceptualizing policy this way, the goal is to understand, and ideally test, how adopting and amending polices may affect implementation of an intervention. Randomized-controlled designs can be used to answer such questions. However, quasi-experimental or simulation modeling approaches are typically more feasible in which outcomes are compared across geopolitical jurisdictions  or health systems that different policies “on the books” at the same time. Many established typologies of implementation strategies conceptualize policy as a strategy to use. Examples include the Expert Recommendations for Implementing Change compendium  , “policyPolicy can be conceptualized in multiple, non-mutually exclusive ways in implementation science. Clear conceptualizations of these distinctions, we argue, are important to advancing the field of policy-focused implementation science and prompting the integration of policy into the field more broadly. This typology offers four ways to conceptualize policy in implementation science, but there are likely additional ways of thinking about policy in the field. We hope that this simplistic typology will serve as a is a point of departure for more policy-focused intellectual exploration, dialogue, and research in the field of implementation science.