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Record W2097814520 · doi:10.1080/01612840600599994

TOWARDS MALECENTRIC COMMUNICATION: SENSITIZING HEALTH PROFESSIONALS TO THE REALITIES OF MALE CHILDHOOD SEXUAL ABUSE SURVIVORS

2006· article· en· W2097814520 on OpenAlexaff
Eli Teram, Carol Stalker, Angela Hovey, Candice L Schachter, Gerri Lasiuk

Bibliographic record

VenueIssues in Mental Health Nursing · 2006
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of AlbertaUniversity of SaskatchewanWilfrid Laurier University
Fundersnot available
KeywordsShameSexual abuseVulnerability (computing)PsychologyContext (archaeology)SocializationHealth careQualitative researchHealth professionalsPerceptionDevelopmental psychologySuicide preventionClinical psychologyPoison controlMedicineSocial psychologySociology

Abstract

fetched live from OpenAlex

This article extends earlier reports of an ongoing qualitative inquiry on childhood sexual abuse survivors' experiences with health professionals. In this paper, we aim to enhance understanding of male survivors' experience. While male and female participants express similar anxieties and fears about their encounters with health professionals, there are gender-based differences related to the perceptions of victimhood and manhood; guilt and shame; homophobia; disclosure of abuse; and the expression of vulnerability. The implications of these differences for sensitive health care practice are analyzed within the context of gender relationships and the differential socialization of men. Malecentric communication is proposed as a method for addressing the specific experiences of male survivors in their encounters with health professionals.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0040.003
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.391
Teacher spread0.363 · 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 designNot applicable
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

Citations47
Published2006
Admission routes1
Has abstractyes

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Same venueIssues in Mental Health NursingSame topicChild Abuse and TraumaFrench-language works237,207