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Girly mags and girly jobs: Pornography and gendered inequality in forensic practice

2012· article· en· W1516024625 on OpenAlexaff
Dave Mercer

Bibliographic record

VenueInternational Journal of Mental Health Nursing · 2012
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPornographyPerformative utteranceContext (archaeology)PsychologySociologySocial psychologyCriminologyEpistemologyPsychoanalysis

Abstract

fetched live from OpenAlex

This article presents findings from a discourse analytic study into the constructive nature and textual variations of language in a high-security hospital. It explores how mental health nurses, and men convicted of sexual offences who also have a diagnosis of personality disorder, talked about pornography and sexual crime in the context of forensic provision. Access to sexually-explicit media, in relation to treatment environments for people convicted of sexual offences, has become a cause for professional and political concern in the UK. Data collection and analysis, undertaken concurrently, were informed by a discursive design. Semistructured interviews, as co-constructed accounts with nursing staff and detained patients, were audio-taped and transcribed. Data were coded to identify the discursive repertoires, or collective talk, of respondents. In contrast to empirical inquiry into pornography and sexual violence, methodology shifted attention from measurement to meaning, and situated research in a clinical domain. The findings focus on performative language use, where talk about pornography textured the treatment environment, contributed to an overtly masculine discourse, framed the ward as male space, and promoted gendered inequality. The discussion questions the legitimacy of the therapeutic enterprise.

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)0.001
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 score0.408
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.072
GPT teacher head0.458
Teacher spread0.387 · 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

Citations18
Published2012
Admission routes1
Has abstractyes

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