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Record W4408281793 · doi:10.3390/sexes6010011

Ecological Contexts of Resilience in Sex Work: Managing a Precarious, Stigmatised, and Criminalised Occupation in One Canadian City

2025· article· en· W4408281793 on OpenAlexafffundabout
Andrea Mellor, Cecilia Benoit, Brett Koenig

Bibliographic record

VenueSexes · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsResilience (materials science)Work (physics)EcologyPsychological resilienceGeographySociologyPsychologyEngineeringBiologySocial psychologyPhysics

Abstract

fetched live from OpenAlex

This paper explores the ways that sex workers in one Canadian city cultivate resilience in their workplaces. In 2017–2019, a period following the enactment of Canada’s revised prostitution law, a cross-section of active sex workers (N = 59) from Victoria, Canada, were interviewed about what they do to keep safe in their sex work jobs, including what they do before or during dates, how their strategies for safety have changed over time, how they draw on their larger networks, and what resources they wish they could access to improve their abilities to remain safe. Using an ecological framework of resilience, our findings show that, despite job precarity, stigma, and criminalisation, participants were actively involved in developing strategies to keep safe at work. Their resilience is a combination of factors unique to each worker’s social location and their access to workplace safety measures, including screening techniques and tools, diverse social networks, and safe working locations. We call for a public health approach to sex work that builds on workers’ strengths and enacts policies that aim to dismantle the structural environments of risk in their occupation.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.023
GPT teacher head0.307
Teacher spread0.284 · 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 designObservational
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

Citations1
Published2025
Admission routes3
Has abstractyes

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