Bibliographic record
Abstract
Citizenship, social rights and social cohesion: A priori, the concept of social cohesion evokes the idea of a body of values, norms, behaviours and expectations that, because they are shared, give meaning to “living together”. This is why, at a time of globalization, neo-liberalism, and economic growth at all costs, implementing strategies designed to promote social cohesion is often presented as the antidote to the ills of society and the prerequisite to development. In the literature and political discourse, the concept of social exclusion is used to describe the reality of many social groups today who feel deprived of security and identity and are convinced that they have lost something they once possessed. The question, then, is one of knowing what the obstacle to social cohesion is. Research efforts, as well as international institutions, have abundant recourse to this logic in order to identify and remedy some of the obstacles they perceive as being the causes of social exclusion. For example, in this respect, inclusion and participation in the labour market is the object of sustained attention; the same applies to the war against poverty. Meanwhile, everything points to social exclusion and its opposite, social cohesion, being phenomena that cannot, for the purpose of analysis, be reduced to questions of material dysfunction in a given society. By the same token, social cohesion cannot be reduced to a matter of integration or a fight to leave the margins of society. This is only part of what we learn from the work of Jane Jenson and Mateo Alalouf, whose earlier efforts have inspired several contributions that follow.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.453 | 0.226 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".