MétaCan
Menu
Back to cohort
Record W3004626941 · doi:10.1017/lsi.2019.50

A Case of Love and Hate: Four Faces of Alienation Among Young Lawyers in France and Switzerland

2020· article· en· W3004626941 on OpenAlexaff
Isabel Boni-Le Goff, Éléonore Lépinard, Nicky Le Feuvre, Grégoire Mallard

Bibliographic record

VenueLaw & Social Inquiry · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAlienationTypologyGlobalizationSociologyCompetition (biology)Social psychologyPolitical sciencePsychologyLaw

Abstract

fetched live from OpenAlex

Over the past three decades, the legal profession has experienced globalization, the rise of mega-law firms, and intensified competition. These transformations have been associated with declining career perspectives, the hyper-specialization of legal work, and increased levels of stress. We argue that the concept of alienation offers valuable insights into these changes by providing an original analysis of the objective and subjective experiences of early career lawyers at work. We elaborate a multidimensional typology that covers the content and retributions of legal work. By categorizing experiences of alienation along these two axes, we identify four ideal-types of alienation: powerlessness, purposelessness, time deprivation, and unfairness. Based on qualitative studies carried out in France and Switzerland, we illustrate how young lawyers differentially experience each type of alienation, according to gender, status, and firm size. We conclude by suggesting how these factors combine to produce long-terms effects, such as the high female attrition rates observed in the Swiss and French legal professions.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0260.019
Scholarly communication0.0060.003
Open science0.0010.008
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.136
GPT teacher head0.317
Teacher spread0.181 · 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 designQualitative
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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueLaw & Social InquirySame topicGender Diversity and InequalityFrench-language works237,207