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Record W2595476103

Introduction: Regulating Decent Work for Domestic Workers (Introduction: Réguler le travail décent pour les travailleuses domestiques)

2011· article· fr· W2595476103 on OpenAlexaff
Adelle Blackett

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicInternational Labor and Employment Law
Canadian institutionsMcGill University
Fundersnot available
KeywordsDomestic workEmpowermentAgency (philosophy)Context (archaeology)Work (physics)Political scienceLabour lawSociologyPublic relationsLawSocial scienceGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

This introductory article has two dimensions that are addressed simultaneously. First, it focuses on the international developments, to highlight and explore some of the findings of the International Labour Organization's (ILO) law and practice report on Decent Work for Domestic Workers. Second, it reflects on the contributions in this special issue to the broader deliberative process of identifying and critiquing labour regulatory frameworks as an empowerment strategy for historically marginalized women, such as domestic workers. This introduction suggests that a labour regulatory framework that both secures domestic workers rights in context and creates an enabling framework to support domestic workers' exercise of agency is a crucial part of a reconstructionist project, which that may accompany, but is not a substitute for, a broader project of social transformation.

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)0.003
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0130.007
Insufficient payload (model declined to judge)0.0110.004

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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
GenreEditorial

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

Citations0
Published2011
Admission routes1
Has abstractyes

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