Scientific Production on the Social Economy: A Review of Worldwide Research
Bibliographic record
Abstract
Abstract The aim of this article is to assess the use of the term Social Economy, while being aware of its lack of concreteness, and to analyze the level of scientific production by means of a bibliometric analysis using WoS (JCR) and Scopus (SJR) as sources. Starting in 2004 and related to the Charter of Principles of the Social Economy, the material development of articles began. The most receptive countries are Spain, the USA, China, the UK and Canada. In terms of the most productive journals, Voluntas in JCR and CIRIEC-Spain and REVESCO in SJR stand out. Scientific production on this issue is linked to university institutions, namely the Chinese Academy of Sciences, the University of Valencia and the University of Quebec. The most prevalent subject are Economics and Business in the case of JCR and Social Sciences in SJR. The most recognized term is that of cooperatives and the most prevalent keyword trends being related to sustainable development, climate change, urbanization, management and China.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.031 | 0.048 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".