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Record W2300372181 · doi:10.2196/publichealth.4742

Intragroup Stigma Among Men Who Have Sex with Men: Data Extraction from Craigslist Ads in 11 Cities in the United States

2016· article· en· W2300372181 on OpenAlexvenueno aff
Tamar Goldenberg, Dhrutika Vansia, Rob Stephenson

Bibliographic record

VenueJMIR Public Health and Surveillance · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyStigma (botany)Social psychologyDemographyAdvertisingCriminologySociologyBusinessPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Gay, bisexual, and other men who have sex with men (MSM) regularly experience homophobic discrimination and stigma. While previous research has examined homophobic and HIV-related intergroup stigma originating from non-MSM directed at MSM, less is known about intragroup stigma originating from within MSM communities. While some research has examined intragroup stigma, this research has focused mostly on HIV-related stigma. Intragroup stigma may have a unique influence on sexual risk-taking behaviors as it occurs between sexual partners. Online sexual networking venues provide a unique opportunity to examine this type of stigma. OBJECTIVE: The purpose of this study is to examine the presence and patterns of various types of intragroup stigma represented in Men Seeking Men Craigslist sex ads. METHODS: Data were collected from ads on Craigslist sites from 11 of the 12 US metropolitan statistical areas with the highest HIV/AIDS prevalence. Two categories of data were collected: self-reported characteristics of the authors and reported biases in the ads. Chi-square tests were used to examine patterns of biases across cities and author characteristics. RESULTS: Biases were rarely reported in the ads. The most commonly reported biases were against men who were not "disease and drug free (DDF)," representing stigma against men living with HIV or a sexually transmitted infection. Patterns in bias reporting occurred across cities and author characteristics. There were no variations based on race, but ageism (mostly against older men) varied based on the ad author's age and self-reported DDF status; bias against feminine gender expression varied based on self-reported sexual orientation; bias against "fat" men varied by self-reported DDF status; bias against "ugly" men varied by a self-report of being good-looking; and bias against people who do not have a DDF status varied based on self-reported HIV status and self-reported DDF status. CONCLUSIONS: Despite an overall low reporting of biases in ads, these findings suggest that there is a need to address intragroup stigma within MSM communities. The representation of biases and intragroup stigma on Craigslist may result from internalized stigma among MSM while also perpetuating further internalization of stigma for men who read the sex ads. Understanding patterns in the perpetuation of intragroup stigma can help to better target messages aimed at making cultural and behavioral shifts in the perpetration of intragroup stigma within MSM communities.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.093
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.048
GPT teacher head0.356
Teacher spread0.308 · 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 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

Citations12
Published2016
Admission routes1
Has abstractyes

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