Editorial: Gratitude for Nonprofit and Social Economy Studies
Bibliographic record
Abstract
La publication phare de l'Association de recherche sur les organismes sans but lucratif et l'économie sociale (ARES), la Revue canadienne de recherche sur les OSBL et l'économie sociale a été bâtie sur les fondements et les valeurs de l'économie sociale, y compris un accès libre, un engagement envers le bilinguisme, et une communauté accueillante.Cette communauté continue à grandir, signalant ainsi la force de la mise en relation des universitaires et praticiens dans notre domaine.Nous sommes particulièrement enthousiastes à l'égard des nouveaux chercheurs suivant cette tradition et de la recherche de pointe qu'ils sont en train de faire.Nous remercions tous ceux et celles qui ont collaboré à cette revue et contribué à ce domaine au fil des années.Dans ce numéro, vous retrouverez trois articles dans la section « Perspectives » ainsi que cinq articles de recherche évalués par les pairs.Dans le premier des trois articles « Perspectives », John R. Whitman pose la question suivante dans le contexte d'une pandémie persistante : « Ce choc a-t-il éveillé les OSBL sur As the premier journal of the Association of Nonprofit and Social Economy Research (ANSER), the Canadian Journal of Nonprofit and Social Economy Research was built on the foundations and values of the social economy, with open access, a commitment to bilingualism, and a welcoming community.This community continues to grow, a great testament to the strength of the connection between academic and practitioner scholars in our field.We are especially excited about the entry of new scholars to this tradition and the cutting-edge research they are producing.Many thanks to all of the contributors to the journal and to the field over the years.In this issue, you will find three Perspectives pieces and five peer-reviewed Research articles.In the first of the three articles in the Perspectives section, John R. Whitman asks the following question in light of the ongoing pandemic, "Has this shock provided Editorial / Éditorial (Autumn / automne
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".