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Record W2589238121 · doi:10.1080/13642987.2016.1260007

Long-term adverse outcomes from neonatal circumcision reported in a survey of 1,008 men: an overview of health and human rights implications

2017· article· en· W2589238121 on OpenAlexaff
Tim Hammond, Adrienne Carmack

Bibliographic record

VenueThe International Journal of Human Rights · 2017
Typearticle
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsHarmHuman rightsAutonomyBioethicsMedicineBodily integrityPsychologyPolitical scienceLawSocial psychology

Abstract

fetched live from OpenAlex

Amid growing bioethical and human rights concerns over non-therapeutic infant male circumcision, calls have been made to investigate long-term impacts on the men these infants eventually become. The present inquiry attempts to identify factors contributing to concerns of men claiming dissatisfaction with or ascribing harm from neonatal circumcision. This large sample size survey involved an online questionnaire with opportunities to upload photographic evidence. Respondents revealed wide-ranging unhealthy outcomes attributed to newborn circumcision. Survey results establish the existence of a considerable subset of circumcised men adversely affected by their circumcisions that warrants further controlled study. Empirical investigations alone, however, may be insufficient to definitively identify long-term effects of infant circumcision. As with non-therapeutic genital modifications of non-consenting female and intersex minors, responses are highly individualistic and cannot be predicted at the time they are imposed on children. Findings highlight important health and human rights implications resulting from infringements on the bodily integrity and future autonomy rights of boys, which may aid health care and human rights professionals in understanding this emerging vanguard of men who report suffering from circumcision. We recommend further research avenues, offer solutions to assist affected men, and suggest responses to reduce the future incidence of this problem.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.160
GPT teacher head0.450
Teacher spread0.290 · 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

Citations62
Published2017
Admission routes1
Has abstractyes

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