MétaCan
Menu
Back to cohort
Record W4324141148 · doi:10.1111/lasr.12643

What makes an international institution work for labor activists? Shaping international law through strategic litigation

2023· article· en· W4324141148 on OpenAlexaff
Filiz Kahraman

Bibliographic record

VenueLaw & Society Review · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsUniversity of Toronto
FundersUniversity of WashingtonNational Science Foundation
KeywordsLawPolitical scienceInstitutionJurisprudenceInternational lawMobilizationSociology

Abstract

fetched live from OpenAlex

Abstract Studies on international legal mobilization often analyze the mobilization efforts of activists at a single international court. Yet we know little about how activists choose among multiple international institutions to advance social justice claims. Drawing on comparative case studies of Turkish and British trade union activists' legal mobilization efforts and case law analysis, I show that activists, guided by their lawyers, probe multiple avenues to identify the legal institution with the highest judicial authority and is most responsive to activists' claims. Once they identify their target institution, the iterative process between a responsive court and activists' strategic litigation can build a court's jurisprudence in a new issue area, even if the court provides limited de jure rights protections. Activists primarily use international litigation strategy to leverage structural reforms at the domestic level and to set new international norms through precedents.

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)0.014
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0120.030
Scholarly communication0.0280.013
Open science0.0020.009
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0130.002

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.

Opus teacher head0.167
GPT teacher head0.335
Teacher spread0.168 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueLaw & Society ReviewSame topicHistorical and Contemporary Political DynamicsFrench-language works237,207