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Record W4393987466 · doi:10.26522/ssj.v18i2.4382

Threats, Victims and Unimaginable Subjects of Rights: A Genealogy of Sex Worker Governance in Poland

2024· article· en· W4393987466 on OpenAlexvenueno aff
Agata Dziuban

Bibliographic record

VenueStudies in Social Justice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
FundersNarodowym Centrum NaukiEuropean Commission
KeywordsCorporate governancePolitical scienceSex workersSociologyGender studiesLawGenealogyHistoryDemographyEconomicsManagement

Abstract

fetched live from OpenAlex

This paper sketches the emergence of, and shifts within, the social, legal, and political figurations of sex workers in Poland. By adopting a genealogical perspective, I investigate how sex workers have been (re)constituted as subjects of governance and unimaginable social justice claimants in legislation, political debates, and law enforcement strategies. With a broad temporal scope, this article traces continuities, transformations, and disruptions within modes of sex work governance in Poland from the adoption of the first laws relating to sex work enacted during the early 19th century to the present day. Through analysis of policy documents, scholarly work on the history of sex work policies in Poland, and personal accounts by sex workers, I identify and examine two dominant discursive and legal figurations of a sex worker: as a threat, and as a victim in need of rescue and protection. While analysing the emergence of and interplay between these two figurations, this article demonstrates how these seemingly contradictory frames of recognition gradually conjoined within 20th-century Polish sex work governance strategies, rendering sex workers unimaginable subjects of rights and social justice claimants.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.026
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.370
Teacher spread0.342 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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