Catégorie socioprofessionnelle, identité, engagement social et usage des médias. Analyse d'une dynamique complexe
Bibliographic record
Abstract
Cet article examine la relation entre le secteur dans lequel les individus travaillent et le niveau de leur profession, d'une part, et, d'autre part, le rapport qu'ils entretiennent avec les médias, y compris Internet, en fonction des usages qu'ils en font. Il se penche aussi sur l'identité sociale, en mettant diverses manifestations en relation avec la manière dont les individus vivent leur rapport aux médias. Il remet en question l'hypothèse d'une forte association entre le niveau professionnel et le rapport aux médias. Il met en évidence des phénomènes complexes d'homogénéisation et de différenciation sociales. Les données proviennent d'un échantillon de travailleurs qui ont répondu à un questionnaire centré sur le rapport aux médias. This article examines the link between the domain and level of occupation, on the one hand, and use of media, including internet, on the other. It adds to this investigation an analysis of identity in its relation to media use and accessibility. It challenges the hypothesis of a strong correlation between level of occupation and use and accessibility to media. It reveals complex phenomena of social homogenization and differentiation. Data is extracted from a sample of workers who completed a questionnaire which focused on use of media.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".