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Record W4283652380 · doi:10.1080/17441692.2022.2092187

Exploring the impact of military conflict on sex work in Ukraine: Women’s experiences of economic burden

2022· article· en· W4283652380 on OpenAlexafffund
Lisa Lazarus, Nicole Herpai, Daria Pavlova, Maureen A. Murney, O. M. Balakireva, Tatiana Tarasova, Leigh M. McClarty, Michael Pickles, Sharmistha Mishra, Evelyn L. Forget, Marissa Becker, Rob Lorway

Bibliographic record

VenueGlobal Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsSt. Michael's HospitalThe Scarborough HospitalUniversity of TorontoUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsWork (physics)Meaning (existential)Sex workPerspective (graphical)Theme (computing)Qualitative researchPolitical scienceSociologyGender studiesEconomic growthPsychologyMedicineSocial scienceHuman immunodeficiency virus (HIV)Economics

Abstract

fetched live from OpenAlex

Little is known about the impact of military conflict on sex work from the perspective of sex workers. We attempt to explore the meaning of conflict on sex work by asking women about the changes that they have experienced in their lives and work since the beginning of the 2014 military conflict in eastern Ukraine. The findings in this article are based on qualitative interviews with 43 cisgender women living and practicing sex work in Dnipro, eastern Ukraine. Our analysis highlights the meanings that sex workers have linked to the conflict, with financial concerns emerging as a dominant theme. The conflict therefore functions as a way of understanding changing economic circumstances with both individual and broader impacts. By better understanding the meaning of conflict as expressed by sex workers, we can begin to adapt our response to address emerging, and unmet, needs of the community.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.077
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.087
GPT teacher head0.364
Teacher spread0.277 · 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 teacher head, 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

Citations6
Published2022
Admission routes2
Has abstractyes

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