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Record W2618344933 · doi:10.1080/13691058.2017.1328075

Sex work and three dimensions of self-esteem: self-worth, authenticity and self-efficacy

2017· article· en· W2618344933 on OpenAlexaffabout
Cecilia Benoit, Michaela Smith, Mikael Jansson, Samantha Magnus, Jackson Flagg, Renay Maurice

Bibliographic record

VenueCulture Health & Sexuality · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSelf-esteemSelf worthPsychologySocial psychologySelf-efficacySelfPsychology of selfDiversity (politics)Thematic analysisSelf-conceptWork (physics)Qualitative researchSociology

Abstract

fetched live from OpenAlex

Sex work is assumed to have a negative effect on self-esteem, nearly exclusively expressed as low self-worth, due to its social unacceptability and despite the diversity of persons, positions and roles within the sex industry. In this study, we asked a heterogeneous sample of 218 Canadian sex workers delivering services in various venues about how their work affected their sense of self. Using thematic analysis based on a three-dimensional conception of self-esteem - self-worth (viewing oneself in a favourable light), authenticity (being one's true self) and self-efficacy (competency) - we shed light on the relationship between involvement in sex work and self-esteem. Findings demonstrate that the relationship between sex work and self-esteem is complex: the majority of participants discussed multiple dimensions of self-esteem and often spoke of how sex work had both positive and negative effects on their sense of self. Social background factors, work location and life events and experiences also had an effect on self-esteem. Future research should take a more complex approach to understanding these issues by considering elements beyond self-worth, such as authenticity and self-efficacy, and examining how sex workers' backgrounds and individual motivations intersect with these three dimensions.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.039
GPT teacher head0.366
Teacher spread0.327 · 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.

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

Citations48
Published2017
Admission routes2
Has abstractyes

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