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Travailleurs des plateformes numériques de services : quelles garanties sociales ?

2018· article· fr· W2910741655 on OpenAlexvenueno aff
Jean-Michel Servais

Bibliographic record

VenueInterventions économiques · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Les débats sur la protection sociale des personnes travaillant par l’intermédiaire de plateformes numériques de fourniture de services se focalisent sur la nécessité de protéger ces derniers même s’ils ne sont pas liés à un employeur par un contrat de travail. Le caractère précaire de leur situation apparaît quand ils dépendent pour leur subsistance d’un ou de quelques entrepreneurs. La problématique se rapproche de celles, soulevées depuis longtemps, d’autres travailleurs dont le statut juridique de salarié ou d’indépendant est, comme la leur, incertain ; cela inclut ceux de l’économie informelle des pays en développement. L’examen de ces expériences éclaire la discussion actuelle sur les garanties à accorder aux personnes dont il est ici question, sur les possibilités ouvertes par cette comparaison, mais aussi ses limites. Il conduit à explorer de nouvelles voies.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0030.004
Scholarly communication0.0070.010
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0380.003

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.

Opus teacher head0.085
GPT teacher head0.337
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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