Bibliographic record
Abstract
La question de l'egalite se retrouve au coeur des problematiques traitant de democratie et d'espace public, depuis l'antiquite grecque ou les affaires publiques etaient abordees au sein de l'agora entre egaux, ce qui n'empechait pas d'exclure par la meme femmes et esclaves, jusqu'a l'espace public moderne ou l'exclusion est demeuree longtemps de mise, sous pretexte que seuls les citoyens liberes de contraintes economiques et autres, etaient susceptibles de raisonner au nom de la collectivite. Dans le cadre de cet article, nous abordons la question de l'egalite a propos des usages de l'Internet a des fins de participation a l'espace public. Nous nous interesserons a la fois aux usages collectifs a travers l'etude des sites d'organismes et aux usages individuels a travers celle de la participation a des listes de discussion. L'espace public cree par ces utilisations de l'Internet s'ouvre progressivement a un plus grand nombre de groupes et de personnes, mais il accepte egalement de plus fortes inegalites entre ceux-ci. On comprend des lors que les organisations militantes qui luttent pour une diminution des inegalites a travers le monde s'interrogent quant a leur appropriation collective du reseau informatique.
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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".