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Record W3014072786 · doi:10.3917/chii.168.0110

Uber et Cabify, opérateurs de plateformes numériques ou entreprises de transport avec chauffeur ?

2020· article· fr· W3014072786 on OpenAlexaff
Francisco Trillo

Bibliographic record

VenueChronique Internationale de l IRES · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’Espagne, à la suite des conflits entre taxis et VTC provoqués par le lancement d’UberPop en 2014, est le pays qui a rendu possible l’arrêt prononcé par la Cour de justice de l’Union européenne en décembre 2017, statuant que l’activité d’Uber relevait d’une prestation de service de transport et non d’intermédiation ou d’information. La question de la nature de la relation contractuelle avec ses chauffeurs, qui lui est intimement liée, n’a en revanche pas été tranchée même si la probabilité est forte pour que les tribunaux se prononcent en faveur de l’existence d’un lien de subordination.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.028
GPT teacher head0.286
Teacher spread0.258 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

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