The concept of wholeness or oneness refers to not only humans, but also all of creation. Similarly, consciousness may not wholly exist inside the human brain. One consciousness could permeate the whole universe as limitless energy; thus, human consciousness can be regarded as limited or partial in character. According to the limited consciousness concept, humans perceive projected waves or wave-vortices as a waveless item. Therefore, human limited consciousness collapses the wave function or energy of particles; accordingly, we are only able to perceive them as particles. With this “limited concept”, the wave-vortex or wave movement comes into review, which also seems to have a limited concept, i.e., the limited projected wave concept. Notably, this wave-vortex seems to embrace photonic light, as well as electricity and anything in between them, which gives a sense of dimension to our brain. These elements of limited projected wave-vortex and limitless energy (consciousness) may coexist inside our brain as electric  and quantum (diffused oneness of waves) brainwaves, respectively, with both of them giving rise to one brain field. Abnormality in either the electrical or the quantum field or their fusion may lead to abnormal brain function. Our universe and brain obviously require energy. Energy is described in many ways and comprises chemical, metabolic, radiation, and many other types. In physics, energy has been noted as having one peculiar feature—ups and downs. This wavy form of energy is thought of as covering our entire universe, including our body and brain. This idea came about after realizing that an atom or light can exist in two forms, both as a particle and as a wave ,3,4,5,6.In 2019, the present corresponding author published a manuscript that described waveless energy . WavelesAccording to the aforementioned concept of these three energies , the authors discuss and explain (a) the possible relationship that might exist between waveless and wavy energy in our universe and brain, and (b) the projected wave concept (vortex), which could explain (1) the duality of an atom, (2) our borderless universe, (3) the absence of wave interference in our three-dimensional (3D) physical universe, (4) the infinite shape  of materials in our brain and nature, and (5) the existence of two energy fields (electromagnetic and quantum fields) inside our universe, as well as inside our brain, which could explain the pathogenesis of neurological (particularly psychiatric) disorders. Through this perspective, the authors hope that future directions in research will focus on quantum field and quantum energy detectors for the brain, which may further enhance our understanding of brain function, thereby facilitating the cure of more diseases.Energy conservation is a principle in physics. There is no loss of energy; it is only converted to different forms. From the time of singularity, the total energy has been maintained but in different forms. Previously, we explained the possible existence of infinite light, frequency, or energy prior to the Big Bang . This liY-axis describing infinite waveless energy (with the absence of spacetime: “zero” spacetime) gives rise to another source of infinite energy, i.e., the X-axis describing infinite wavy energy with the presence of “infinite” spacetime or infinite dimension. Therefore, these two infinite energies are inter-related, and the total energy is always preserved: one in the vertical or Y-direction  with waveless, timeless, spaceless, and limitless energy, and the other in the horizontal or X-axis infinite direction with the presence of spacetime or dimension. In addition, one may notice at least two possible transitional points in X-axis (finite time and space). This wavy and finite energy formed our current 3D universe . Thus, one may say that the wavy infinite energy which was initially derived from waveless infinite energy was the building stone for our physical or 3D universe. From a broader perspective, electromagnetic photonic light (photonic light vortex/light immediately after the singularity) was initially thought of as arising from an implosion and explosion  of this infinite wavy energy ; subsequently, our 3D universe came into complete existence via projected waves of infinite wavy energy that ‘intersected’ the initially formed electromagnetic photonic light to form electricity and matter . One important question related to the mind is the following: “Does our physical universe really exist?” Because of the peculiar features of our brain, this sort of question is commonly asked by many scientists ,14. We aX-axis (limitless or infinite in spacetime or dimension), whilst infinite waveless energy has infinite energy in any (infinite) direction. It is represented here as the Y-axis in The aforementioned discussion stated that all things can apparently be described as waves (wavy energy), which originate from infinite wavy energy or, on a deeper level, from infinite waveless energy or an infinite light. This infinite wavy energy is limitless on a single On the basis of the above argument, is it possible then that our 3D physical universe is not limitless, but instead a ‘limited or finite physical universe’? The reason for saying this is because of the limited wave-projection concept . Since all things can be regarded as waves, then perhaps one should also wonder why all these wave signals do not bump into each other. The reason that these waves do not collide is that they only appear to us to across the same region of space or the same dimension , whereas, in reality, this is not the case. The medium in which these waves exist might consist of more than three dimensions . However, humans have evolved to live with organs of vision that allow us to only view things in three dimensions. The next question then becomes the following: “How can a medium with more than three dimensions exist, while the universe that we observe through our eyes is only made up of three dimensions?” This is because what we observe as humans, using the sense organ that we know as our eye, is not a complete, correct representation of the environment. What we observe is a projected reality, projected energy, or ‘limited part’ of reality (waves/energy/dimension).The limited projection of reality (energy) is due to the limited number of waves projected onto our physical universe . BecauseIn summary, this intersection  has apparently created an illusion of physical materials (hologram); they are actually waves  but appear as matter (vortex of matter), light, and electric vortices. This idea may explain why atoms or light existing in our physical universe can exist either in particle (matter is illusion) or wave form , i.e., a duality feature. Hence, one may conclude that an illusion of physical material is created by (a) the limited projection of waves and (b) the limited consciousness of the brain. As mentioned before, limitless consciousness exists as one entity, i.e., one consciousness (wholeness). Therefore, it also encompasses our brain consciousness. According to this argument, one may, hence, view our brain consciousness as not truly representing one whole consciousness. It is only partial or limited. Therefore, one may say that the human brain has limited consciousness. Similar to the ‘limited projected waves’ concept that was previously discussed, one may notice that the word ‘limited’ again appears in our discussion. Thus, with this limited consciousness concept that exists in our brain, we gain a glimpse of the original wave function of particles when collapsed. Thus, one cannot see the original waves (or energy); what we instead see are illusionary vortices of the limited projected waves. Since our interpretation of reality is represented by continuous waves or quantum energy (not particles or matter), our notion is that ‘discreteness arises from continuousness when observed by the mind (brain)’.Since the brain is also encompassed by the oneness of consciousness (infinite wavy energy), one may presume that the brain features infinite waves. It is delocalized and in diffusion with external cosmos waves. In fact, it can be viewed as one medium of oneness, one field, wholeness, or one consciousness ,19,20,21The electrical wave brain network  is commonly studied and is easily evoked by physical stimuli. Projected waves (limited waves) or vortices which form physical stimuli cause evoked responses inside the brain, which is theorized here as having only limited consciousness ; furthermore, the brain itself is a part of the projected wave-vortices. Thus, one may say that the ‘electrical wave brain network’ represents a kind of mirror to ‘limited projected waves’ . With this view, i.e., considering the presence of limitations in both wave projection and consciousness, larger evoked electromagnetic fields are naturally observed for seeing, hearing, tasting, etc., of material objects ,24. At tThe subsequent question one might ponder is the following: “Is there any interaction between the electrical wave field  and quantum–light wave field  inside the brain?” In our opinion, the interaction between these two fields is always present because they originate from the same infinite wavy field, which is diverted into two arms  and finally converges in the brain. This interaction may cause various states. The electrical wave field (evoked fields) dominates with respect to our five senses that are related to matter or projected fields , whereas a possibly larger role is played by the quantum–light wave field in cognitive processes such as language, memory, attention, emotion, and anxiety . A disturbed interaction, disharmony, or chaos (decoherence) between these two fields, as well as a reduction or increment in quantum neuroanatomical waves/energy , may lead to various diseases, as seen in some psychiatric disorders where an ‘exit from reality’ or ‘break in wholeness’  is commonly present ,30,31,32In a nutshell, both electrical and quantum–light fields are needed to sufficiently study brain function. In other words, one may say that the brain has both an electromagnetic field (EMF) or electric field (EF) and a quantum field (QF) or quantum–light field (QLF); alternatively, it can be said that the brain has both high-EF and low-QF waves. According to our new perspective on brain function, infinite waveless energy is an infinite frequency (energy) that is not related to time or space. It gave rise to another infinite energy, called infinite wavy energy, which is related to infinite space–time or dimension. Since time is only relative, new finite wavy energy (our universe) with a ‘new period of time’ can be formed via a second transition. The formation of new finite wavy energy/physical universe (started with the light) has resulted in the subsequent intersection of various waves coming from higher infinite wavy energy/waves/dimension. These intersections manifest themselves as various infinite-shape vortices that follow the laws of biology and physics. These vortices range from light to electricity. Matter and other vortices are included in between. Therefore, matter can be regarded as an illusion or can appear as either particles or waves . This concept also explains our physical universe (finite wavy energy) as having no border. In reality, it is part of an infinite wavy energy/universe and, thus, the noted physical universe expansion could in fact be a consequence of our brain activity, which has partial consciousness . In essence, a person with limited brain consciousness cannot reach the border (no border or no question as to what substance the universe expanding into) of this illusionary universe . According to these principles, our brain is thought of as having two types of brainwaves or energy: (1) quantum–light waves, which permeate and interact with the whole universe , and (2) the electromagnetic field or electric field , which corresponds to a limited or finite projected wave (finite wavy energy) with a larger evoked response when stimulated. Thus, the brain can be regarded as an incomplete mirror to our cosmos (limited projected wave-vortices resulting in EMF and part of a more diffused QF). This manuscript ends with


Since most evaluations of intergenerational programs (IGPs) focus on the perspective of a single stakeholder group concerning the benefit for themselves, we compared perceptions of multiple stakeholders: older adults, younger adults, and IGP organizers concerning the impact of IGPs on older and young participants. Using a mixed-methods approach, we collected data from thirteen community-based IGPs. The quantitative analyses included a comparison of the different stakeholder groups via ANOVAs and chi-square analyses. In order to identify the reasons for different attribution ratings among stakeholders, we conducted a qualitative analysis of the stakeholders’ comments and responses to open-ended questions using a thematic analysis approach. Overall, participants rated benefits to themselves lower than attributed to them by their counterparts. Differences in ratings may be explained by differences in expectations and needs, cognitive dissonance, as well as a lack of awareness about other participants’ experiences. Given the discrepancies in perception of impact, it is vital to seek input from all stakeholders in order to understand their respective needs and expectations, construct a balanced evaluation, and improve IGP processes and outcomes. Studying a single stakeholder group for project evaluation is likely to provide only one perspective, whereas including all points of view provides a more complete picture. An aging population that is headed toward outnumbering younger generations raises a range of challenges and requires responses by communities and policymakers . One resPrevious studies have reported beneficial outcomes of community- and school-based IGPs for younger persons (YAs), such as improved social skills and acquisition of new knowledge ,5,6,7,8,OAs also reported benefits of community- and school-based IGPs, such as improved physical and cognitive activity ,18, incrTwo studies that reported IGP organizers’ evaluations of IGPs described multiple benefits, including enhancing enjoyment, increasing confidence, improving health, reducing isolation , improviMost of the literature examined either OAs’ perspectives ,29,30,31To our knowledge, however, no study has examined the perspectives of all three stakeholders—OAs, YAs, and organizers—on the impact of a particular IGP, on themselves, and on the others involved in the program. Studying how each stakeholder group perceives the program’s impact on itself and on other stakeholder groups is crucial for evaluating programs as a whole, and for gaining a fuller understanding of how IGPs affect their participants. Therefore, our study sought to examine (1) how different stakeholders perceive an IGP’s impact on themselves and on others. After finding significant differences among the respective perceptions via quantitative analysis, we further examined (2) the reasons for differences in these perceptions through a qualitative analysis of questionnaire responses.We interviewed 84 OAs, 96 YAs, and 21 organizers who were involved with one of 13 IGPs which were designed as community-based experiences for YAs and OAs who met about once a week on average. These IGPs fell into two types based on their content and goals:Topic-focused IGP type. These programs included a variety of activities focusing on a specific subject: community theater (group 1), intergenerational dancing (2), learning how to play bridge (3), learning photography skills (4), and joint studying of Jewish religious texts (5). Participants in the topic-focused groups included 47 OAs and 32 YAs.Assistance IGP type. These programs facilitated one-to-one encounters between YAs and OAs, such as YAs visiting OAs’ homes, and providing them with assistance in their daily routines (group 6), a program that specifically sought to promote intergenerational relationships (7), YAs writing OAs’ memoirs (8 and 9), YAs visiting holocaust survivors in their homes (10), Israel Defense Force soldiers visiting an OA at the OA’s home or at a senior club (11), YAs teaching OAs how to use computers and the Internet (12), and YAs assisting OAs with pet care (13). The assistance groups involved 37 OAs and 64 YAs.Data were collected through questionnaires developed on the basis of a literature review and discussions with IGP organizers prior to the initiation of the study. Separate questionnaires were developed for OAs, YAs, and organizers. After obtaining participants’ informed consent, questionnaires were either completed in a personal interview by trained interviewers with an academic degree in the social sciences or were self-administered (completed via an online survey or a printed questionnaire completed by hand). When questions were left unanswered by interviewees, research staff contacted them and followed up on those questions. The in-person interviews were transcribed during the interviews.The questionnaires began with demographic and background questions including age, gender, and education. Subjective health was rated from 1 (poor) to 5 (excellent) based on the global self-rated health item on the SF-36 .The Impact of Intergenerational Programs Questionnaire  asked aWe compared the three stakeholder groups  by displaying means, conducting ANOVAs for ordinal and interval level data, and using percentages and chi-square for nominal level data using IBM® SPSS® Statistics 26. We used ANOVAs to compare the ratings of the respective stakeholder groups concerning the impact of the IGP on various outcome variables separately for YAs and OAs. We used the Benjamini–Hochberg method  in orderIn a previous analysis of some of these data , we compThe responses to open-ended questions were analyzed using thematic analysis  to elucip ≤ 0.01 for all).The background characteristics of the stakeholder groups are described in As to informants’ ratings of the impact of IGPs on themselves and others, organizers reported a greater positive impact on nearly all measures as compared to the reports of OAs and YAs see . When exEarlier analyses of data from this sample revealed that there were significant differences between topic-focused IGPs and assistance type IGPs in OAs’ self-report of decrease in boredom and decrease in loneliness . Thus, iOur qualitative analysis examined the transcripts of the participants’ responses to open-ended questions in order to clarify the reasons for different attribution ratings among stakeholders.Organizers described their job as difficult, citing the pressures of marketing their program  and matching each YA with an OA quickly. “Filtering is hard work, and you have to focus on this. Otherwise, it’s a nightmare for the OAs and for the coordinators and for the YAs too, and that would be a pity because the project is really good” .Some organizers attributed challenges to characteristics of OAs and YAs, or to the matching of OAs and YAs: “Sometimes there are individual difficulties, or the match between the young and old is not good, or the OA does not fully understand what it [an IGP] is [about]” . Or: “Some young people do not really fit; they do not have much patience. Adults - it’s hard for them to bring strangers [into their homes]” . Often the organizers have no control over who participates in the program, or they feel they must take anyone who agrees to participate because of shortages of YAs, resulting in mismatches and ongoing tension: “For the young women, the difficulty is poor personal discipline, difficulties in understanding the world of old age […]. We get young women from all kinds of homes and backgrounds, and they do not always have sufficient mental maturity to accept situations of crisis, illness, health crises, losses and death experienced by the OA. The personal guidance [we offer] is very much related to the young women’s willingness to share [their experiences] with the coordinator, and in some cases, I do not know about things that happen” .In the quantitative analysis, participants tended to rate benefits to themselves lower than they were rated by their counterparts. For example, in the case of the YAs’ self-assessments, they gave the enjoyment and self-esteem variables the lowest ratings. This might be explained by external stress that YAs experience and which affects their IGP experience. For example, one YA described the time-pressure of IGP participation: “Recently I had the exam period. I know that the [IGP] meetings are supposed to be regular, but there is nothing one can do about it. I work two jobs; now I work in three because I do not have exams” .Other stressors that YAs reported included feelings of sadness about the OAs’ condition: “It’s difficult to see them [OAs] depressed and to try to improve their mood; it’s also hard to hear difficult stories or to cope with silence” . Other YAs were mindful of the proximity of OAs’ deaths: “I find the issue of death difficult. Two weeks ago, two people from the club passed away-suddenly I realized with what population I work” .Others felt powerless to handle the OAs’ needs. “Sometimes the OAs talk about things that are too difficult to take in. I have my own difficulties that I need to deal with. But I cannot tell them [I have had] ‘enough’ because I cannot contain it” . These types of stressors diminished the level of IGP benefit felt by YAs, but they were not reported by OAs and were hardly recognized by organizers.Understandably, OAs were focused on their own needs: “It’s a help, I need these things… I have no one else to do it… Previously, my children did it, and now they are married and live far away. I do not want to burden them” . The stress expressed by some YAs contrasted with the sense of comfort sometimes expressed by OAs: “I’m not alone; it’s the most important thing” .YAs and organizers rated the benefits to OAs as to decrease in boredom, opportunity for adding social relationships, and decrease in loneliness higher than OAs did for themselves. For example, some OAs said they felt an activity’s effect was only short-term: “The day she arrives, I’m happy. But only on that day” . OAs complained that some YAs were unreliable and unpunctual: “Some young people are late, and I don’t like it” .Disappointed expectations were also reflected in YAs’ complaints about OAs’ behavior and neediness: “Difficulties exist in facing an OA because it is difficult to set boundaries for them. They want, for example, that I stay on after the meeting or that I will visit them even outside of the activity hours” .In the quantitative findings, there was an exception to the pattern that others’ ratings of benefits tended to be higher than self-ratings. When OAs assessed the benefits to YAs in the areas of decrease in boredom, adding interest to life, and opportunities to enhance social relationships, OAs provided lower ratings than did YAs. This may have been influenced by a perception that YAs are naturally busy. Some OAs expressed awareness of YAs’ multiple commitments and the time pressure upon them: “I understand it’s another age and she’s very busy” , or “You suddenly notice all the difficulties experienced by young people, a lot more is demanded from them than was demanded from us when we were young. The tasks and commitments are much harder for them” .Notwithstanding their misgivings, YAs described how IGPs added to their lives in ways not mentioned by other stakeholders. “The activity contributes to the feeling that I am doing something for other people, especially the older adults. Their loneliness at this age is so painful and I’m glad I have an opportunity to relieve it for a few hours” (#157-21-F-assistance). This sentiment concerning YAs was rarely expressed in the qualitative data from OAs and was not reported by organizers.Similarly, some YAs found that participation in IGP activities enriched their understanding of the world: “I think I learn a lot from them, whether it’s hearing about things they think, or it’s hearing about things they’ve experienced, about history, understanding about people and emotions… and beyond that, I learned a lot about myself” .For many YAs, the relationship they developed with the OAs was rewarding in the sense of providing a novel and emotional connection: “I think it’s very interesting to have a relationship like this, between someone [who is] 18 years old and a 60-year-old woman. This is unusual and does not happen much unless it’s a relative. It’s very special” .Our results revealed three types of discrepancies in perceptions among OAs, YAs and organizers regarding perceptions of benefits to OAs and YAs: (a) organizers tended to provide the most beneficial ratings; (b) in general, the respective participants rated benefits to themselves lower than their counterparts attributed to them; and (c) contrary to the general trend in our results, OAs attributed lower ratings to YAs’ improvement in the variables of decrease in boredom, adding interest to life, and adding social relations than YAs rated for themselves.In attempting to explain these discrepancies, it may be suggested that organizers presented the most positive image of their programs and their work because they may be the most invested stakeholders. Cognitive dissonance may be at work as well, since organizers may need to feel that their work is valuable in order to justify their involvement in a difficult job for which they often feel undercompensated.Participants tended to rate benefits to themselves lower than their counterparts did, probably because individuals are more aware than others of the limitations of the benefits for themselves. IGP participants tended to focus on their own perspectives and concerns. For example, while OAs appreciated receiving assistance within an IGP, they were concerned that the program might be terminated and expressed disappointment when the YA could not visit . Our finThe exception to the overall trend in our results tended to occur when stereotypes obstructed individuals’ appreciation of benefits to others. Specifically, YAs may have overestimated the benefits felt by OAs in the variables of loneliness and decrease in boredom because YAs perceived OAs as dependent, lonely, and bored ,38. ConvThe hurdle to mutual understanding between younger and older IGP participants could potentially be mitigated through better matching of OAs and YAs and better provision of guidance and training for them. Our data indicated that even organizers are stressed and constrained in their ability to improve intergenerational understanding due to a lack of funding and resources, as was also described by Ayala et al. (2007) , and insA strength of this study is the sample size, which is larger than that of most studies of IGPs. The use of multiple programs was not only necessary to obtain the sample size but likely enhanced generalization. As all of the IGPs were in Israel, more research is necessary to achieve greater generalization to other contexts.Our research demonstrates not only how different stakeholders in IGPs perceive the benefits and challenges of the programs differently, but also how they attribute different levels of program impact to their fellow stakeholders. The value of such results is especially significant because the vast majority of IGP evaluations utilize only one point of view. It is vital to seek input from all stakeholder groups whenever possible in order to achieve broader and more telling insights into IGPs’ impact.This study demonstrates the importance of seeking input from all stakeholders in order to understand their respective needs and expectations, construct a balanced evaluation, and improve the processes and outcomes of IGPs. Using a single stakeholder group for project evaluation provides only one perspective, whereas including diverse groups provides a more complete picture. For this reason, and considering the differences in benefits perceived by various stakeholders, it seems that self-report by one stakeholder provides an incomplete picture. Studying the gaps in perceptions is useful for improving our understanding of each stakeholder group, and helping OAs, YAs and organizers understand each other. This point is best demonstrated by OAs’ significant underestimation of the contribution of IGPs to decreasing YAs’ boredom and loneliness, reinforcing the idea that the study of discrepancies among perspectives is an effective tool for evaluating and improving IGPs.


Since China’s reform and opening-up in 1978, the income of rural residents has increased when compared with that of urban residents. However, the income growth rate of farmers is relatively low, and the income gap between urban and rural areas is widening. Using a sample of 1,325 large-scale farming households in Lin’an, this study constructs a theoretical path for how the level of vertical integration and an organization model affect farmers’ income levels and empirically tests the path using a mediation effect analysis model. The results indicate that organization models and vertical integration are important factors that affect farmers’ income levels. The total income and agricultural operation income of farmers who participate in agricultural operation organizations are greater than that of farmers who do not participate in an operation organization. In addition, the total income and agricultural operation income of farmers who produce and process and those who produce, process, and sell are higher than those of farmers who only produce. A farmers’ organization model has both a direct and an indirect positive influence on their income level, with the indirect positive influence coming through the mediating variable of vertical integration. The application of the organizational model can promote the growth of rural households’ total family income and agricultural income by 13.48% and 14.48% respectively, consisting of direct increases of 9.67% and 10.19%, and indirect increases of 3.81% and 4.29% through vertical integration. The results also show that access to credit, agricultural technology training, and the farmer’s education level have significant positive impacts on farming income levels. The findings suggest ways to increase farmers’ income by perfecting agricultural management organization systems, promoting agricultural industrialization, strengthening rural financial support, improving agricultural technical training for farmers, and increasing their level of education. Improving farmers’ income is the key to solving issues facing agriculture, rural areas, and farmers , 2. ChinPromoting a diversified agricultural organization model and strengthening the vertical integration of agriculture are considered by the government to be important measures to promote the organic integration of small- and large-scale farming and to increase farmers’ income. The vertical integration of agriculture is the coordinated contact method of the successive stages of the production and marketing of agricultural products in the vertical system of the supply chain . TheoretSince 2013, the Chinese government has emphatically promoted the development of new agricultural business entities to increase farmers’ income, mainly through farmer cooperatives, agricultural enterprises, and family farms. They encourage farmers to cooperate with new business entities to increase agricultural income. As of 2018, there were 2.17 million farmer cooperatives legally registered in China, and more than 100 million peasant households had joined the cooperatives, accounting for 49.1% of China’s total peasant households. In 2017, average operating income of each cooperative was about 23.29 million yuan and the distributed profit was nearly 3.38 million yuan . This inSome scholars have studied the impact of cooperative economic organizations on farmers’ incomes. These studies generally affirm that cooperative economic organizations are beneficial to farmers’ income. For example, a study of farming organization models finds that a cooperative economic organization can purchase production resources uniformly and provide standardized production technology to ensure the quantity and quality of agricultural product outputs, increasing farmers’ incomes –15. As aIn terms of industrialization, existing studies show that vertical integration of agriculture can also increase farmers’ income. For example, some scholars examine the action principle between rural industrial structure and farmers’ incomes and quantitatively analyze their degree of correlation. They find that industrialized agricultural operations promote continuous extension of the industrial chain, which promotes employment of the rural surplus labor force, significantly improving peasant household income levels , 20. In Existing research has laid a strong foundation for this study, but there are also some deficiencies. First, most studies focus on either the organization model or vertical integration in isolation, ignoring the inherent correlation between the two. Second, there are few theoretical analyses of the relevant influence mechanism in existing studies. Moreover, there are few empirical studies based on large samples of farmers, and thus, the reliability of the research conclusions needs to be further verified. To address these gaps, this study examines vertical integration, employs a mediation effect analysis model and empirically tests the influence of vertical integration on organization models and their impact on farmers’ income levels, so as to provide a beneficial reference to help increase farmers’ income.Since the reform and opening-up, China has introduced household contract management in rural areas and a two-tiered management system combining unification. This has, for the most part, liberated productivity in China’s countryside, and farmers have become independent producers and operators. However, the contradiction of small farmers in a large market still exists; most households have no organization and suffer from the disadvantage of a passive position in the market. They not only have to bear the risks of natural disasters and policy, but also face greater market risks. Consequently, since the 1990s, China has begun to encourage new agricultural operations through professional farmers and large family farm cooperatives. Compared with traditional smallholders, the new operators are more organized, vertically integrated, and more closely connected to the market, and more of their total income is derived from agricultural operating income. Based on existing literature , this stStudies have shown that improving the degree of organization among farmers, through, for example, cooperatives, companies, and associations , 29, is As cooperatives and companies have a higher degree of industrialization and have more advantages in processing and marketing, when farmers join these organizations, their degree of industrialization will increase correspondingly, and the industrial chain will extend from production to production, processing, and sales , 33. A dAgricultural industrialization, also called “agricultural industry integration,” is described as integrated management of agricultural and industrial production, supply, and marketing, and is the general rule of worldwide agricultural development . IncreasTo summarize, different agricultural organization models have dissimilar effects on farmers’ behavioral efforts, which can directly impact their income levels. In addition, agricultural organizations may indirectly affect farmers’ income levels by promoting agricultural industrialization. This paper proposes the following theoretical hypotheses:H1: The organizational model has a positive effect on increasing farmers’ income.H2: The organizational model promotes the vertical integration of farmers, thereby indirectly increasing farmers’ income.Lin’an, a typical agricultural county in China, is located northwest of the economically developed Zhejiang Province. In 2018, 61% of Lin’an’s population was agricultural and the per capita disposable income of rural residents was 25,598 yuan. The province has nine distinctive and profitable agricultural industries, including bamboo shoots, hickory nuts, and others; the value of the annual production of bamboo shoots and hickory nuts alone is 4.8 billion yuan. The vertical integration of Lin’an’s agricultural and farmers’ organizations is high, and agricultural cooperation is well organized, with integrated production, supply, and marketing. Organizational models such as “agricultural company + farmers,” “farmer cooperative + farmers,” and “agricultural company + farmer cooperative + farmers” play an important role in improving farmers’ incomes. Using farmers in Lin’an to study the impact of vertical integration and organization models on peasant household income can provide significant insights to aid in China’s rural revitalization and industrial poverty alleviation.The study uses the third agricultural census data from Lin’an’s agricultural scale enterprises and includes households whose annual income is mainly from agricultural production and operations and is 100,000 yuan or more. The data are cross-sectional data accurate as of December 31, 2016 and cover Lin’an’s 13 townships, comprising 1,325 farmers. The sample’s main statistical indicators include individual characteristics , household characteristics , and management features .The characteristics of how farmers are organized and their level of vertical integration can be measured by the agricultural operation organizations in which they participate and the production and operation modes they adopt. Based on the situation in Lin’an, a comparative analysis is performed of two forms of agricultural operation organizations, “professional association + farmers” and “farmer cooperative + farmers”; as well as two production and operation models, “production and processing” and “production, processing, and sales.”“Professional association + farmers” agricultural management organizations in Lin’an are mainly involved in bamboo, hickory, and other industries of professional economic associations. All professional associations are non-profit organizations whose members are mainly agricultural operating units and farmers engaged in work related to production and operations related to agricultural products. The income of the associations can only be used to develop the association, and cannot be distributed among members. Their primary function is to provide farmers with unified technical guidance and training, before, during, and after production, and with unified sales of agricultural products to improve farmers’ self-management levels. “Farmer cooperative + farmers” organizations in Lin’an are mainly professional cooperatives for industries such as bamboo shoots, hickory, and others. All cooperatives are non-profit organizations, with farmers comprising over 80% of the membership. In addition to providing technical training for members and a marketing channel for agricultural products, these cooperatives seek to obtain economic benefits by developing agricultural production and members, in accordance with the amount and distribution of surplus, which is more beneficial for primary producers.Lin’an mainly processes bamboo shoots, hickory nuts, and other agricultural products, with the economy in the process of gradually transforming from primary processing to refined processing. “Production and processing” refer to the production and operations by which farmers sell their agricultural products to distributors after primary processing; distributors then process these products and sell them to end consumers. “The biggest food bamboo garden in South China” is a motto that articulates Lin’an’s advantages in its bamboo industry development. However, some farmers fail to master the fine processing technology, and continue to treat their own bamboo shoots as primary agricultural products without processing or with simple processing, and sell them directly. Therefore, under the “production and processing” operating mode, farmers’ industrial chains end after the initially processed agricultural products are sold to distributors. The “production, processing, and sales” mode of production and operation refers to farmers who, on the premise of mastering certain processing technologies, carry out the fine processing of the agricultural products produced or create their own brand of agricultural products and directly sell them to end consumers. For example, as the largest hickory processing and sales center in China, Lin’an has distributed its hickory sales outlets to over 20 provinces (cities) by developing regional brands. Local farmers can process their own hickory and sell it directly to end consumers through these outlets. Therefore, the operation mode of “production, processing, and sales” extends farmers’ industrial chains from the primary producer to the end consumer.The characteristics of peasant household operations reflect that different types of agricultural occupations affect income levels differently. The planting industry has the least impact on income, and fishery has the greatest impact. It can be seen from the table that the agricultural and total incomes of households with credit are higher than those of households without credit, while rural financial support is relatively weak, as the proportion of farmers who can obtain credit is only 16.38%. The larger the scale of land operation, the higher the level of household agricultural and total incomes. However, the operating scale of peasant households is generally small, with less than 10% of the actual farmland area being more than 10 mu; there are similar characteristics for transferred land. In addition, the agricultural and total incomes of households with cash crops are higher than those for households without cash crops; about 30% of peasant households plant cash crops.The analysis shows that there is a certain correlation between farmers’ income levels and factors such as organization model and vertical integration. However, determining whether there is a causal relationship requires econometric analysis. Therefore, this study builds an econometric analysis model to empirically analyze how factors such as vertical integration and organization model impact farmers’ income levels.In this study, total household income and agricultural operating income are selected to measure farmers’ income levels. First, based on the function that determines farmers’ incomes , an econy is the farmer’s income level ; organize represents the different forms of organization models, and industry represents different levels of vertical industrialization. xi represents the control variables, which include individual characteristics , household characteristics , operation characteristics , and regional dummy variables. In addition, γ and β are the parameters to be estimated, and ε is a random error term.α1 represents the total effect of the organization model on farmers’ income levels; β1 indicates the effect of the organization model on vertical integration; γ1 indicates the direct effect of the organization model on farmers’ income levels after controlling for the influence of vertical integration; γ2 indicates the effect of vertical integration on farmers’ income levels after controlling for the influence of the organization model. The coefficient product β1γ2 represents the effect of the organization model on farmers’ income levels through vertical integration, that is, the indirect effect. The following relationship exists among the three effects: α1 = γ1+β1γ2. That is, the total effect is equal to the sum of the direct and indirect effects. In addition, xi represents other control variables that affect the degree of organization or farmers’ income levels; and ε, μ, and φ are random error terms. The specific variable names and descriptions are shown in Eqs –4) are  are 4) aIn the analysis, total household income and agricultural operation income are used to represent the income variables. For the large-scale farmers, the total household income and agricultural operation income are 292,600 yuan and 257,200 yuan respectively. Agricultural operating income thus accounts for 87.90% of the total.The categories of participation in agricultural operation organizations are used to represent the organizational model variable. “No participation” is set as the control group and assigned a value of 1; the “farm + association” model is assigned a value of 2. In general, the degree of organization of farmers is not high, with an average of 1.27, and most farmers are only in the relatively low-level organizational model of “professional association + farmers.”The types of production and operation methods are adopted to represent the vertical integration variable. “Production” is set as the control group and assigned a value of 1. “Production and processing” is then assigned a value of 2, and “production, processing, and sales” is assigned a value of 3. In general, the degree of vertical integration of farmers is not high, with an average of 1.27, and there are few production, processing, and sales farmers.Following previous studies –44, the The household head’s gender, age, and years of schooling are selected as household head characteristics. The household head’s gender may affect household decision-making and thus household income. In addition, the older farmers are, the more difficult it is for them to adapt to the new era of development needs, which might lead to making certain household decisions that fail to increase household income. However, the longer farmers attend school, the more human capital they accumulate, which can lead to an increase in household income level.Households with a large labor force have more people engaged in agricultural production and management or non-agricultural work, promoting growth in the households’ income. By contrast, a labor force of higher average age is less physically fit, reducing the likelihood and amount that they will engage in production and business activities, in turn resulting in lower household income. If the labor force’s average years of education is higher, it may lead to a higher level of agricultural or off-farm work, resulting in higher household income levels. However, the population burden coefficient may hinder this growth. Agricultural technology training helps break the bottlenecks of capital and labor in agricultural production and operation, thus raising farmers’ production and incomes. Non-agricultural labor income is generally higher than that of agriculture; the higher the rate of non-farm employment, the more beneficial it is for family income. Social capital accumulation, such as family members working as civil servants, leads to higher peasant household income, because capital is an important factor for promoting production and operation.The main agricultural occupations that farmers engage in will also affect their income. If loans can be obtained through private lending or formal bank credit, higher investment returns are more likely, thus improving household income. Land is one of the key factors in agricultural production and management: the larger the land area owned by peasant households, the more likely they are to carry out scale operations and thus receive a reward of corresponding scale. The transfer of land in or out will affect the scale of land operation and thus also affect income. Compared with food crops, the economic value of cash crops is relatively higher, so it is very likely that farmers who plant cash crops will have higher incomes than farmers who do not.Based on the equation that determines farmers’ income, this study empirically analyzes the impact of different organization model forms and different degrees of industrialization on farmers’ income levels. The results of the model estimation are shown in Model 1 examines how factors such as vertical integration and organization model impact household income, while model 2 examines the impact of these factors on agricultural operations income. The estimation results show that there are no observable differences between the results of model 1 and model 2 in the significance level or sign of the coefficients, indicating that the estimation results are robust.According to the model estimation results, the influence of all three organizational models, including “professional association,” “farmer cooperative,” and “company + farmer cooperative + farmers,” have a significant positive impact on farmers’ agricultural income and total family income, confirming hypothesis H1. The estimated coefficient shows that, when compared with farmers who did not participate in an operation organization, the total household income of farmers who participated in “professional association,” “farmer cooperative,” and “company + farmer cooperative + farmers” increased from 13.22% to 27.70%, while the increase in agricultural operation income ranged from 14.62% to 28.55%. The increase in farmers’ income levels differ depending on the organization model. “Company + farmer cooperative + farmers” is the highest, followed by “farmer cooperative,” and finally “professional association.” Moreover, the same organization model has different effects on different types of farming income, and each organization model has a larger improvement effect on farmers’ agricultural operation income than on total income.The model estimation results also show that the effects of the two production and operation modes on total household income are significantly positive. Thus, compared to production-oriented farmers, both total household income and agricultural operation income are higher for farmers whose production and operations are integrated . Similarly, there are differences in how the level of industrialization affects farmers’ incomes. The effect of production, processing, and marketing integration is greater than that of production and marketing integration. Further, there are differences in the effects of the same mode of production and operation on different income types. Each mode of production and operation has a larger role in increasing farmers’ agricultural income compared to total income.The estimated results show that the household head’s years of schooling, the number of household members in the labor force, their average years of education, their amount of agricultural technology training, whether they include civil servants, their main types of agricultural occupations, access to credit, operating land area, and whether cash crops are planted can all significantly improve their total household income and agricultural income, while the household head’s gender and age, the average age of the labor force, the population burden coefficient, and transferred land area do not significantly affect farmers’ income levels.This study constructs an influence path among vertical integration, organization model, and farmers’ income level. A mediating effect analysis model is used to empirically test the path constructed to determine whether longitudinal integration has a mediation effect; in other words, it is necessary to test whether the path of the theoretical model of the mediation effect is reasonable . TherefoThe first step is to construct a model in which the household’s total income is the explained variable and the organization model and control variables are included as explanatory variables (model 3). If the coefficient of the organization model is significant, it will be argued that the organization model has a mediating effect; otherwise, it will be argued that there is a masking effect. The second step is to construct a model in which vertical integration is the explained variable and the organization model and control variables are included as explanatory variables (model 4). Next, in model 5, the household’s total income is the explained variable, and the organization model, intermediating variables, vertical integration, and control variables are included as explanatory variables. If the coefficient of the organization model in model 4 and the coefficient of longitudinal integration in model 5 are both significant, then the indirect effect is also significant. If at least one is not significant, proceed to step 3; otherwise, skip step 3 and go to step 4. In step 3, a bootstrap method is used to test the null hypothesis that the product of the coefficient of the organization model in model 4 and the coefficient of the longitudinal integration in model 5 = 0. If significant, then the indirect effect is significant—continue to the fourth step; otherwise, stop testing. The fourth step tests whether the coefficient of the organization model in model 5 is significant. If so, the direct effect is significant—continue to the fifth step; otherwise, stop testing, and conclude that the longitudinal integration has a complete mediating effect. The fifth step compares the sign of the coefficient of the organization model in model 5 to the sign of the product of the coefficient of the organization model in model 4 and the coefficient of the longitudinal integration in model 5. If the signs are the same, the vertical integration has a partial mediating effect, and if different, a masking effect.The main purpose of this analysis process is to examine whether vertical integration plays a mediating role in the organization model’s influence on household income. Similarly, using the same explanatory and control variables, household income as the explained variable is replaced by agricultural operation income in models 6 and 7. The same testing procedure is used to test whether vertical integration plays a mediating role in the organization model’s influence on farmers’ agricultural operation income.The test results are shown in In the tests of the mediating effect, first, the organization model is tested to see whether it has a significant influence on total household income and agricultural operation income as the explained variables. In both models 3 and 6, the coefficients of the organization model are significant at the 1% level, indicating that the organization model has a positive impact on farmers’ income levels. Second, the organization model is tested to see if it has a significant influence on longitudinal integration. According to model 4’s estimation results, the coefficient of the organization model where longitudinal integration is the dependent variable is significant at the 1% level, indicating that the organization model promotes improvement in farmers’ vertical integration. Finally, a mediation effect test is conducted based on the estimates in models 5 and 7. After vertical integration, the mediating variables of farm household income and agricultural management organization model are introduced and are significant at the 1% level; moreover, the vertical integration of farmers’ household income and the impact of agricultural management income are also positive and significant at the 1% level. Combined with the above model estimation results, this indicates that vertical integration plays a partial mediating role in the influence of the organization model on total household income and agricultural operation income, verifying hypothesis H2.Having verified the rationale of the path established based on the mediation effect theory, we now calculate values of the effects of the organization model on total household income and agricultural operation income. According to the results, the organizational model can promote the growth of rural households’ total family income and agricultural income by 13.48% and 14.48%, respectively, consisting of a direct increase to income of 9.67% and 10.19% and an indirect increase of 3.81% and 4.29% through vertical integration. The indirect effects account for 28.26% and 29.63% of the total effects. This shows that the mediating transmission mechanism of vertical integration is highly significant to explain the organization model’s impact on farmers’ income levels.Using 1,325 peasant households in Lin’an as its sample, this study applies an econometric model to empirically analyze the impact of organization model, vertical integration, and other factors on farmers’ household income levels. By establishing an organization model incorporating vertical integration and farmers’ income levels, among the three influence paths, we construct a path for empirical testing using a mediation effect analysis model. On this basis, we offer the following conclusions and suggestions.First, the organization model is an important factor that affects farmers’ income levels. Compared to farmers who did not participate in an organization, those who did had better coordination. The incentives and restrictions of the organization system can improve the degree of behavioral effort, which in turn increases farmers’ income levels. In addition, the degree of institutional incentives and constraints in organization models differs, and they have different effects on promoting growth in farmers’ incomes. The government should actively create conditions to encourage and guide farmers to participate in the various types of agricultural management organizations, by establishing an organization to promote its members’ interests, as a linking mechanism to promote increases in farmers’ income.Second, vertical integration is another key factor that affects farmers’ income levels. Compared with production-oriented farmers, “production and processing-oriented” and “production, processing, and sales-oriented” farmers have improved vertical integration, their industrial chain has been extended, there is more in-depth processing of agricultural products, and the distribution channels for agricultural products are more stable, thus increasing farmers’ incomes. In addition, the organization model affects farmers’ income levels not only directly but also indirectly, their income through the mediating variable of vertical integration. Therefore, the government should give full consideration to the role of agricultural operation organizations in promoting agricultural industrialization, supporting and developing various forms of agricultural operation organizations, and promoting the level of agricultural industrialization operations through organizations to improve farmers’ income levels.Third, as a means of rural financing to support agricultural development, agricultural loans play an important role in increasing agricultural production intensity and farmers’ incomes. Agricultural funds are essential for agricultural production and operations. However, the direct financing system for agricultural production in China needs improvement. Moreover, agricultural producers’ capacity to accumulate funds is quite limited, which makes the availability of the funds needed for agricultural production largely dependent on financial institutions. To bolster financial support for the development of modern agriculture, the government can formulate corresponding preferential tax policies for agriculture-related loans to stimulate financial institutions to return to the rural financial markets.Fourth, education level and agricultural technology training have significantly positive impacts on farmers’ income levels. Therefore, improving farmers’ education levels and strengthening training in agricultural technology will help increase their income. The quality of human capital largely determines farmers’ household income. The educational level of those currently involved in production and operations is generally not high, and their enthusiasm for participating in agricultural technical training is generally low; these characteristics seriously hinder the development of modern agriculture and greatly constrain improvement in farmers’ household incomes. The government should therefore strengthen agricultural technical training and education for farmers, to promote the transformation of traditional farmers into new, professional farmers.It should be noted that the data used in this research are cross-sectional, and the level of organization and vertical integration in farmers’ households is a dynamic, changing process. The influence of organization models and vertical integration on farmers’ household incomes also undergoes dynamic adjustment, and may vary from period to period. However, according to the theoretical analysis provided and empirical tests referred to in this study, the significant influence mechanism identified here should exist; more accurate mediation effects can be obtained if the data allow.In addition, this study only considered Lin’an, a typical area in East China, as a case for study, and therefore the generalizability of its conclusions is limited. Lin’an used to be a typical poor mountainous county. However, after China’s reform and opening-up, Lin’an took the lead in developing agricultural zoning and was set on the agricultural development road characterized by agricultural industrialization and management cooperation. Indeed, it has developed from a poor mountainous county into one of the top 100 economically and socially developed counties in China. The per capita net income of farmers increased dramatically from 176 yuan in 1978 to 25,598 yuan in 2018. It was selected as one of the “Top 100 National Comprehensive Strength Counties,” which represent the epitome of China’s rapid agricultural economic development relying on cooperative operations. Nevertheless, its representativeness is still insufficient; in the future, the samples can be expanded to more regions of China, and international comparative studies can also be conducted to comprehensively verify the research conclusions, making them more widely applicable and valuable.S1 Data(XLSX)Click here for additional data file.


This is in exact analogy to the relativity principle as it pertains to the invariant measurement of the speed of light c at the foundation of special relativity (SR). Essentially, quantum information theorists have extended Einstein’s use of NPRF from the boost invariance of measurements of c to include the SO(3) invariance of measurements of h between different reference frames of mutually complementary spin measurements via the principle of Information Invariance and Continuity. Consequently, the “mystery” of the Bell states is understood to result from conservation per Information Invariance and Continuity between different reference frames of mutually complementary qubit measurements, and this maps to conservation per NPRF in spacetime. If one falsely conflates the relativity principle with the classical theory of SR, then it may seem impossible that the relativity principle resides at the foundation of non-relativisitic QM. In fact, there is nothing inherently classical or quantum about NPRF. Thus, the axiomatic reconstructions of QM have succeeded in producing a principle account of QM that reveals as much about Nature as the postulates of SR.Quantum information theorists have created axiomatic reconstructions of quantum mechanics (QM) that are very successful at identifying precisely what distinguishes quantum probability theory from classical and more general probability theories in terms of information-theoretic principles. Herein, we show how one such principle, Information Invariance and Continuity, at the foundation of those axiomatic reconstructions, maps to “no preferred reference frame”  as it pertains to the invariant measurement of Planck’s constant  We will not review such attempts here ”) as it pertains to the invariant measurement of Planck’s constant h when applied to spin-c (light postulate). Thus, the information-theoretic reconstructions of QM  provide a “principle” account of QM in total analogy to that of SR  … The advantages of the constructive theory are completeness, adaptability, and clearness, those of the principle theory are logical perfection and security of the foundations. The theory of relativity belongs to the latter class.We can distinguish various kinds of theories in physics. Most of them are constructive. They attempt to build up a picture of the more complex phenomena out of the materials of a relatively simple formal scheme from which they start out. [The kinetic theory of gases is an example.] Nearly every introductory physics textbook introduces SR via the relativity principle and light postulate without qualifying that introduction as somehow lacking an “interpretation”. With few exceptions, physicists have come to accept the principles of SR without worrying about a constructive counterpart. Thus, a principle account of QM based on NPRF as with SR certainly constitutes an important advance in our understanding of QM. Perhaps prophetically, Bell said ::true intativity”  and evenativity” . Thus, cativity” :By and c at the foundation of SR. Our goal here is to present an equally accessible introduction to the counterintuitive concept of the qubit using the relativity principle and the invariant measurement of h at the foundation of QM, as implied by the reconstructions of QM. Here we will see that the information-theoretic principles of Existence of an Information Unit and Continuous Reversibility  HoweveTo summarize, we see that the reconstruction of QM builds the denumerable-dimensional Hilbert space structure of QM foundationally upon a fundamental 2D object, the qubit. The difference between classical probability and quantum probability then resides in the fact that a pure state can be transformed into another pure state through other pure states in continuous fashion for the qubit, while that is not possible for the classical bit. Of course, this continuously reversible transformation property would also hold for a gbit with In order to argue for the qubit from the gbit, Masanes et al. employed “Continuous Reversibility, Tomographic Locality and Existence of an Information Unit, No Simultaneous Encoding, All Effects Are Observable, and Gbits Can Interact” ,48. In om state” .Per Brukner and Zeilinger ,55, if wc, regardless of their motion relative to the source (light postulate). Here the inertial reference frames are characterized by motion at constant velocity relative to the source and different reference frames are related by Lorentz boosts. Since c is a constant of Nature per Maxwell’s equations, NPRF implies the light postulate (or “NPRF + c” for short)  Thus, Suppose Alice and Bob are making measurements on their particles in the symmetry plane of a triplet state such that on average when they are making measurements in different reference frames (related by SO(3) as shown in h, exactly as length contraction and time dilation are a direct consequence of NPRF + c. We could also partition the data according to Bob’s equivalence relation  inequality precisely to the Tsirelson bound [h. Thus, the reconstructions of QM reveal the relativity principle at the foundation of QM precisely as it exists at the foundation of SR, i.e., demanding the invariant measurement of a fundamental constant of Nature.What we have seen here is that we can explain “average-only” conservation as conservation that results necessarily from Information Invariance and Continuity, which is conservation per NPRF in spacetime, precisely as the relativity of simultaneity results necessarily from NPRF + on bound ,68,69,70Quantum information theorists have a produced a principle account of denumerable-dimensional QM whereby “quantum reality” is characterized most succinctly by the information-theoretic principle of Information Invariance and Continuity. Accordingly, reality is composed fundamentally of discrete bits of irreducible, finite information that can be instantiated and measured physically in 3-dimensional space by measurement devices which are themselves composed of such bits (“closeness requirement”). For the Bloch sphere, Information Invariance and Continuity reflects the fact that it is always possible to create a path from one pure state to another by passing through pure states only, i.e., the surface of the Bloch sphere is composed of pure states. This is quite a “surprising” fact from the point of view of classical probability theory, where the only path in probability state space between pure states is through mixed states with lower information content. The higher-dimensional and multi-particle Hilbert space structure of QM can all be built from this fundamental, “surprising” qubit structure characterized by Information Invariance and Continuity.h, Information Invariance and Continuity entails NPRF + h in exact analogy to NPRF giving rise to the invariant measurement of the speed of light c at the foundation of SR. Of course, it must be the case that NPRF + h is responsible for the non-commutative algebra of the spin measurement operators to begin with.To help clarify the significance of this information-theoretic result, we applied it to the Stern-Gerlach (SG) measurements of a spin-h. So in the classical case, the different measurement operators commute, e.g., h is responsible for the non-commutative algebraic structure of QM, in contrast to the commutative algebraic structure of classical mechanics.To see that, suppose bilistic ,63,64. Th gives us “average-only” projection for measurement outcomes in different reference frames. When applied to Bell state entanglement, we showed that “average-only” projection for one particle leads to “average-only” conservation between two entangled particles in different reference frames. Thus, according to the reconstructions of QM, the mysterious “average-only” conservation of Bell state entanglement, and therefore the Tsirelson bound, follow from conservation per Information Invariance and Continuity, which is conservation per NPRF in spacetime. How conservation per Information Invariance and Continuity bears on other information-theoretic phenomena, e.g., macroscopic entanglement witnesses [Since NPRF (and Information Invariance and Continuity) requires we obtain itnesses ,72,73, iEinstein simply postulates what we have deduced, with some difficulty and not altogether satisfactorily, from the fundamental equations of the electromagnetic field.he nonetheless acknowledged  constructive account of time dilation and length contraction, i.e., there is no “interpretation” of SR. While Lorentz complained wledged