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Record W2998096420 · doi:10.1080/14681811.2019.1703177

From missing to misdirected: young men’s experiences of sex education in Bangladesh

2019· article· en· W2998096420 on OpenAlexaff
Tauhid Hossain Khan, Rebecca Raby

Bibliographic record

VenueSex Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsBrock UniversityUniversity of Waterloo
Fundersnot available
KeywordsPornographyHuman sexualityMasculinityEmbodied cognitionSex educationPsychologyGender studiesSilenceHegemonic masculinitySexuality educationPeer pressureDevelopmental psychologySocial psychologySociology

Abstract

fetched live from OpenAlex

Some sex education research in Bangladesh documents how young people receive sex education but the focus tends to be on the perspectives of teachers and parents; much less is said about how children and adolescents, especially boys, describe their experiences of sex education. This study begins to address this dearth of research. Using a Foucauldian, poststructuralist lens, the study discusses how nine Bangladeshi young men aged 19–24 learned about sex and sexuality during their adolescence, how they interpreted what they learned, and how their learning and experiences reproduce and/or disrupt dominant discourses related to sexuality and sex education. The paper highlights five themes derived from in-depth interviews: silence from parents, lack of school-based sex education, unreliable peer navigators, pornography as a negative force, and the relevance of embodied learning. Of these sources, peers, pornography and embodied learning were the most convenient and common sources of information about sex and sexuality. The study also reveals that what participants learned about sex and sexuality was often strongly gendered (e.g. reproducing hegemonic masculinity and undermining the need for girls’ consent), limited, partial, prohibitive, superficial and unreliable.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0140.010
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.318
Teacher spread0.309 · 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 designQualitative
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

Citations24
Published2019
Admission routes1
Has abstractyes

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