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Record W2255752221 · doi:10.7202/1021840ar

Recherche universitaire et économie sociale en Espagne

2005· article· fr· W2255752221 on OpenAlexaboutno aff
Rafael Chaves Ávila, José Luis Monzón Campos, Antonia Sajardo Moreno, Édith Archambault

Bibliographic record

VenueRECMA · 2005
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La recherche universitaire en économie sociale et coopérative bénéficie en Espagne d’une dynamique positive. Depuis la fin des années 80, les chercheurs intéressés par ce champ sont de plus en plus nombreux, et la communauté scientifique s’organise. Les auteurs étudient dans un premier temps le processus par lequel la recherche s’institutionnalise, à travers le système de recherche-formation-innovation. De son développement dépendent la production scientifique, sa diffusion, mais aussi la motivation des chercheurs à investir le champ, comme en témoigne le contexte espagnol. Dans un second temps, l’article présente un état de la recherche en économie sociale en Espagne à partir, d’une part, d’un répertoire des chercheurs en économie sociale et, d’autre part, d’un recensement des thèses doctorales soutenues dans les universités espagnoles. Principaux thèmes et disciplines de recherche, évolution de l’intérêt pour les différentes familles depuis trente ans, universités les plus porteuses sont ainsi mis en lumière. L’étude est introduite par Edith Archambault, qui effectue un parallèle avec le contexte de la recherche en économie sociale dans d’autres pays, comme la France et le Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0050.010
Scholarly communication0.0140.008
Open science0.0010.006
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0400.009

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.

Opus teacher head0.161
GPT teacher head0.398
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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