Crowdsourcing d’activités inventives et frontières des organisations1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Le crowdsourcing d’activités inventives (CAI) consiste à externaliser à une foule des activités de recherche, des tâches complexes ou créatives. Plusieurs exemples récents ont mis en avant les avantages de ce type de pratique, aussi bien pour réduire les coûts du processus d’innovation que pour améliorer ses résultats. Dans ce travail, nous étudions l’impact organisationnel du CAI en mobilisant les théories sur les frontières des organisations. La littérature identifie quatre frontières différentes : frontière d’efficience, d’influence, de compétence et d’identité. L’analyse en termes de frontière des organisations nous permet notamment de mettre en avant certaines limites du recours au CAI et d’élaborer des prédictions théoriques sur les conditions d’émergence et d’utilisation du CAI.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it