La subjectivité dans la numérisation : les perspectives des professionnels
Bibliographic record
Abstract
L’influence de la subjectivité sur les processus de sélection en matière de numérisation n’a pas encore été étudiée en profondeur. La présente étude traite des facteurs subjectifs qui sous-tendent les choix des professionnels engagés dans des projets de numérisation ; entreprend une réflexion sur la manière dont ils prennent des décisions de sélection et examine dans quelle mesure leurs points de vue influencent les sélections. Des entrevues menées auprès de cinq professionnels des bibliothèques ou centres d’archives révèlent six facteurs subjectifs récurrents. La documentation de l’influence de ces facteurs apporte davantage de clarté, offrant une meilleure compréhension des objets numériques.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".