Rodrigo Carelli, Patrick Cingolani et Donna Kesselman, Les travailleurs des plateformes numériques : regards interdisciplinaires, (Teseo), 2022 : https://www.teseopress.com/lestravailleursdesplateformesnumeriques/
Bibliographic record
Abstract
Introduction 1 L'ouvrage collectif et interdisciplinaire de Carelli et al. (2022) prend pour objet d'tude le travail de plateforme (partie 1) et plus prcisment la figure mergente du chauffeur de VTC 1 (partie 2). Sous les prismes du droit, de l'conomie et de la sociologie, les auteur.e.s scrutent les recompositions des relations d'emploi et de travail qui ont suivi le dveloppement rapide et massif des plateformes de travail la demande. Plus prcisment, ils et elles mobilisent, tout en le questionnant, le concept de zones grises d'emploi et de travail . Nous verrons que les acceptions et usages du concept sont divers, au sein mme de cet ouvrage. Dans un premier temps, on peut simplement indiquer qu'il permet d'interroger la pertinence des catgories binaires de salariat et d'indpendance (ou de travail salari et travail indpendant).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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 teacher head, 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".