The social construction in scientific communities

Building a human community goes through various phases ranging meaning and dynamics of exclusion-elements-and agglomeration and, necessarily leads to different processes of identification and social cohesion within any social group in question. Some of these elements are extremely difficult to measure, but its concrete aim is such that its absence entails vacuum of sociability itself and the collapse of social systems themselves. Some of these elements are cooperation, reciprocity, solidarity, resilience, friendship, empathy and trust, among others. These elements express a common interest shared and integrated by mutual agreement, so inputs and confidence are vital to the continuity of experience in community. In this direction, according to ^{White et al. (2000)}, social integration, at any scale, depend... first of interpersonal connections and after the redundancy of such connections ^{Castaingts (1996)}.

According to ^{De la Rúa (2003)}, inputs such as friendship are generated daily and are represented at different levels of social reproduction in order to confirm and strengthen the significance of social identity, sharing interests, ideas, common goals, social support at times of crisis, and so on. This feeds interaction processes knowledge and opportunities that are both similar subjects, as with those subjects in their dissimilarity are complementary to the subject in question.

In the above context, the construction of scientific communities experiencing similar screens, so the elements that give place are elements of both subjective and objective character.

Scientific agglomeration, based on the management of social inputs (such as trust, reciprocity, cooperation and solidarity), it is a fact that marks the different academic communities and building knowledge networks, to the extent that the structures of collaboration multiply, diversified and, in the interests of individuals and the environment in which they find themselves. Hence, in reference to the academy can talk about strategic alliances networks, broadcast networks, social networks on the internal movement of academic groups, networks of synergy (personal skills that reinforce and enhance the potential development of new ideas and processes), institutional networks of experts (leading research), information networks, customary networks, among many others.

Meanwhile, in the context of the citation, ^{Milard (2010)} indicates the presence of a tendency to homophilia between authors and authors cite its references, from the point of view of discipline, geographical origin or institutional affiliation.

In this direction, ^{Garfield (1996)} commented that, the main reasons for citing other works are: a) pay tribute to the pioneers; b) give credit to related works (tribute to colleagues); c) identification methodologies; d) readings provide support, e) correction of own work; f) correct the work of others; g) criticize previous work; h) substantiation reviews and comments; i) indicate future research; j) to provide query paths badly scattered and poorly cited papers; k) data authentication and type of events; l) identification of the original publications in which an idea or concept; m) discussed the identification of the original publications that describe a concept or eponym; n ) refute the work or ideas of others. Other possible reasons, according to ^{López (2010)} are knowledge of the language is written work and access to these jobs.

This could observe in collaborative processes expressed through articles in scientific journals published, belonging to areas of knowledge that are critical and strategic for countries like Mexico, that is, the agricultural area. Such is the case of the Mexican Journal of Agricultural Sciences of the National Research Institute of Agricultural Livestock and Forestry (INIFAP).

Nodal degree or degree

The nodal degree refers to the sum of all direct ties that has a certain actor (^{Molina et al., 2006}) therefore expresses its position (and potential influence) with respect to other individuals in the social network; therefore, a certain access to the information flow produced in their social group and its level of sensitivity to it. For this work regards the degree indicates the number of co-authorship that each ego has with other nodes. ^{De la Rosa et al., 2005} suggests the mathematical expression for analysing the perspective of the link is:

Where: Aij = matrix linking the nodes "i" and "j"; Di = centrality (degree) of the actor in question

Betweenness degree or intermediation

A widespread assumption in the social sciences is that social structure all actors are potentially linked (^{Wasserman, 1994}; ^{Molina et al., 2006}). Thus, this category allows viewing-analyse those actors who possess the peculiarity of linking groups or actors, therefore, important to help or hinder achieving linking actors influence and determine the processes of cohesion of a community influence given. Calculating centrality measure is performed through the following mathematical equality (^{De la Rosa et al., 2005}).

Where: gk= degree of mediation (betweenness); gij=number of geodesic distances (number of links from one actor to another to reach the target actor) from the "i" node to the "j" node; gikj=number of links between "i" and "j" and passing through "k".

Degree of proximity or closeness

Closeness or proximity is a category with which it is able to measure the distance of each node with the rest. I.e., the ability of a node to reach the other nodes of the network, therefore the chances of reaching (and communicatively influence) to others, and have a quick "access" to information circulating in the social structure. Calculating the closeness it is achieved by summing the geodesic (shorter existing social paths) of each node with the rest. This creates the notion of distance allowing, in turn, calculate its reciprocal, i.e. proximity. In this sense, ^{Brandes (2011)} mentions that the proximity is the inverse of distance and is calculated by dividing the value "1" of the sum of the geodesic (distance).

Where: dG(v, t)= is the geodesic distance (or Geodetic links - minimum Euclidean distances or routes) between the actor "v" and "t".

Clique

In every social structure, there are sub-groups defined by a much stronger cohesion among its members that they may have with members of other groups in the same social structure. For example, in terms of friendships is not unusual for groups defined by identifying elements that established one, the closer (age, gender, race, ethnicity, religion, ideology, tastes, etc.) and ending in groups very well defined in ARS, known as cliques. In this context, a clique is the maximum number of actors sharing all possible links existing between them (^{Hanneman et al., 2005}); hence the canon of a cohesive group is a clique and properties of such sub-structures are: that is perfectly dense, compact and connected. According to ^{Brandes and Erlebach (2005)} one of the mathematical expressions for identification is:

In this context, there would be a clique size k between G.

The Mexican Journal of Agricultural Sciences (REMEXCA)

The process of generating or build a scientific journal aims to influence the dissemination of research results from different regions and countries. For this, protocols and criteria for editing and publication of submitted papers are set. But also, this construction involves a process of linking research communities from different areas of knowledge, from different institutions and countries.

This gives guideline to analyse the process of linking the various authors which opens a complex social universe built based on diversified inputs confidence about the generation and publication of scientific articles in the REMEXCA. This social structure has different angles publications visualization and analysis, as discussed above: agglomerates by researchers working groups by area of knowledge, by institution and nationality; a social structure energized by the management input of trust between the various participating groups (Figure 1) and where researchers from the areas of plant breeding (blue), Rural Development (black), Economics (wine), horticulture (lime stand ) Hydrosciences (pink), Plant Nutrition (white), among others.

Elaboración con datos de REMEXCA-INIFAP.

Figure 1 Social Complexity in scientific collaboration in REMEXCA-INIFAP (2010-2015). 

This social structure is nourished by the processes of collaboration between researchers, which gives rise to a series of observations on the dynamics and constitution. In the analysis of the data was observed that there cooperation between researchers in fields similar knowledge but also dissimilar. While most of the generated collaborations between researchers in the same area of knowledge (78.07%), there are also interventions from different areas, for example, between two areas (14.45%), including 3 areas (4.22%) or 4 areas (1.66%) (Table 1).

Table 1 Diversity of areas in collaboration with co-authors. REMEXCA-INIFAP (2010-2015). 

Elaboración con datos de REMEXCA-INIFAP.

This indicates the presence of cross-fertilization processes of knowledge between researchers, working groups, between institutions and between fields of knowledge. In the data analysed this fertilization is generated primarily from the areas of plant breeding, rural development and biotechnology are the areas that yielded the strongest links (Figure 2) and entomology, soil science and climate change, among others.

Elaboración con datos de REMEXCA-INIFAP.

Figure 2 Collaboration between areas of knowledge. REMEXCA-INIFAP (2010-2015). 

In this way it is possible to detect a structure with various levels of centralization where the first four actors have an average nodal degree of 46.5, the next group of 10 actors, is averaging 24.3 nodal degree (Table 2) and the bulk of the population analysed a nodal degree of ≤ 19.

Table 2 Nodal degree (≥ 20) on authors and co-authors of the REMEXCA-INIFAP (2010-2015). 

Elaboración con datos de REMEXCA-INIFAP.

This has some correspondence with the degree of intermediation calculated as social structure in this unequal distribution of intermediation between social subjects was observed, but with a centralizing trend. For example, only in the case of three actors grades higher intermediation (≥ 1 000) were obtained, another important group constituted actors with a degree of intermediation ranging between 600 and 950 points (Table 3). A third group of 24 actors had average grades intermediation 2 128.

Table 3 Degree of intermediation author and co-authors the REMEXCA-INIFAP (2010-2015). 

Elaboración con datos de REMEXCA-INIFAP.

Making a cut in the quality of the nodal degrees, we only selected those actors with a better or equal to 2 nodal degree, dispensing with those actors who had the character of "political supporter" and considering only those who established communication links in a Central and with a profile of "continuum" lattice. This yielded a more compact but more accessible to analyse and identify more clearly linking processes and reciprocity inside (Figure 3) image.

Elaboración con datos de REMEXCA-INIFAP.

Figure 3 Social Communication Network REMEXCA-INIFAP (2010-2015). Continuum linkage (degree ≥ 2). 

In calculating the nodal degree to this structure, the image obtained can observe the "inside" link, where we can appreciate a more equitable distribution of social prominence and leadership among actors, but also between areas of knowledge, being the present process in these areas of leadership, of plant breeding (blue), hydrosciences (pink) and horticulture (gray) and climate change (brown) (Figure 4).

Elaboración con datos de REMEXCA-INIFAP.

Figure 4 Nodal degree (degree ≥ 2). REMEXCA-INIFAP (2010-2015). 

Proximity (Closessness)

Reciprocity and trust in REMEXCA-INIFAP (2010-2015)

This social structure, like all the others that are generated in social reproduction are managing systems where subjects, and multiple differentiated way, different types of inputs such complex sociality such as inputs trust established for build communities. In the case of this structure of scientific collaboration (Figure 5) shows a dynamic reciprocity (in red) and confidence (thickness of the link) very particular because although there is a trust, with varying degrees of intensity, including researchers, this is varied and not all in all of them there is reciprocity, despite the trust that might have of each other. Furthermore, this reciprocity is given, preferably where there is a higher density of links, therefore, the actors with dominant degrees.

Elaboración con datos de REMEXCA-INIFAP.

Figure 5 Analysis of reciprocity (red) and trust (thickness of the link) with degree between collaborators REMEXCA-INIFAP (2010-2015) (degree ≥2). 

Meanwhile, the intermediation category indicates the ability of some actors to link actors and groups that have a direct link, making them potentially leading questions of legitimacy and power distribution. In this case, particularly in the field of flow of inputs, such as trust and reciprocity, they are managed in a much more locally so having a high degree of intermediation, does not necessarily mean having a high degree of trust and reciprocity (therefore legitimacy).

This is why trust is such a flexible, horizontal input that one can speak of a trust between individuals but also of trust as social pattern. In this direction, in Figure 6 is shown that, the actor with the rank of major intermediation has a certain degree of trust and reciprocity with their peers; however, actors with lower levels of intermediation and greater reciprocity is also seen and even confidence.

Elaboración con datos de REMEXCA-INIFAP.

Figure 6 Analysis of reciprocity (red) and confidence (thickness of the link) with intermediation between collaborators REMEXCA-INIFAP (2010-2015) (degree ≥2).