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The Exploitation of Women Workers

2016· book-chapter· en· W2417510560 on OpenAlexaff
Ishrat Sultana

Bibliographic record

VenueAdvances in linguistics and communication studies · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsYork University
Fundersnot available
KeywordsClothingFactory (object-oriented programming)Virtuous circle and vicious circleHuman rightsColonialismModernityBusinessPolitical economyMarket economyPolitical scienceLawSociologyEconomics

Abstract

fetched live from OpenAlex

The recent series of man-made accidents in Bangladeshi garment industries are highly disturbing to the collective conscience of human beings. These accidents point not only to the poor construction of the factory buildings but also to the invisible tie between the insatiable need for cheap clothing on the part of western consumers and the unlimited greed of the local industry owners. Because most of the workers are economically desperate women and the industries are operated by a capitalist system that denies the rights of women, a systemic exploitation results. Drawing upon the recent tragic events of the deadliest industry disasters in Bangladesh, this paper examines how the industry owners perceive, and practice, ‘human rights'? It also investigates whether neo-colonial modernity is merely exploiting women while pretending to improve their economic conditions, and finally, to what extent female industry workers can overturn the vicious circle of exploitation to establish their rights.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.053
GPT teacher head0.367
Teacher spread0.314 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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