L’appel à un laboratoire en sciences sociales par une agence
Bibliographic record
Abstract
David Gracia, chef de projet webmarketing en poste lors de l’étude, Agence Publika Entretien conduit par Alexandre Coutant, Professeur, Université de Québec à Montréal Cette contribution rend compte de la démarche d’appel à un laboratoire de sciences sociales par l’agence Publika. David Gracia, Chef de projet webmarketing en poste au moment de la réalisation de l’étude, décrit le type d’intervention fourni auprès de leurs clients à travers ce cas, afin d’identifier les situations où une approche académique leur est apparue nécessaire. Alexandre Coutant, responsable des interventions du laboratoire, ajoute ses commentaires, identifiés en italique, aux passages qui lui apparaissent charnières dans l’établissement d’une relation mutuellement profitable.
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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.016 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".