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Record W2144661669 · doi:10.1177/0886260504274340

Sex Work Research

2005· review· en· W2144661669 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Interpersonal Violence · 2005
Typereview
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsConcordia University
Fundersnot available
KeywordsSex workConfidentialityDichotomyPopulationWork (physics)PsychologyGrounded theorySex workersHuman factors and ergonomicsPoison controlCriminologySocial psychologySociologyComputer securityQualitative researchComputer scienceMedicineEngineeringResearch methodologyHuman immunodeficiency virus (HIV)Social scienceEpistemologyDemographyEnvironmental health

Abstract

fetched live from OpenAlex

The challenges involved in the design of ethical, nonexploitative research projects with sex workers or any other marginalized population are significant. First, the size and boundaries of the population are unknown, making it extremely difficult to get a representative sample. Second, because membership in hidden populations often involves stigmatized or illegal behavior, concerns regarding privacy and confidentiality are paramount and difficult to resolve. In addition, they often result in challenges to the validity of the data. Third, in spite of evidence to the contrary, associations between sex work and victimization are still strong, dichotomies remain prevalent, and sex workers are often represented as a homogeneous population. Drawing on three research projects in which the author has been involved-all grounded in a sex-as-work approach-as well as the work of others, this article provides several strategies for overcoming these challenges. Clear guidelines for ethical, nonexploitive methodologies are embedded in the solutions provided.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.142
GPT teacher head0.485
Teacher spread0.343 · 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