Interférences et biais en enquête sociale, issus de l’emmagasinement de réminiscence des conversations qui lui sont apparentées
Bibliographic record
Abstract
L’exécution d’un entretien en enquête sociale se heurte à plusieurs écueils parmi lesquels, et c’est cela la matière développée dans le présent article, les interférences et les biais issus de l’emmagasinement de réminiscence des conversations qui lui sont apparentées. Cette étude soutient que l’espace communicationnel kinois n’est pas une eau qui dort. Il est plutôt rythmé par des vagues de banalisation et de rationalisation qui mettent en mal l’exploitation régulière de l’entretien d’enquête sociale. En outre, l’étude propose un schéma de gestion efficace et efficiente de cette épreuve à mettre à contribution par les chercheurs en sciences sociales.
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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 | 0.014 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".