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Record W4417506161 · doi:10.1177/00220345251392073

Beyond Demographics: Sex, Gender, and Sexuality in Oral Health Research

2025· review· en· W4417506161 on OpenAlexaff
Abbas Jessani

Bibliographic record

VenueAdvances in Dental Research · 2025
Typereview
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsWestern University
Fundersnot available
KeywordsHuman sexualityPsychosocialCurriculumReproductive healthConstruct (python library)Health careAccountabilityHealth policyHealth education

Abstract

fetched live from OpenAlex

Sex, gender, and sexuality are crucial and interrelated factors influencing oral health outcomes, yet they are often overlooked and inadequately addressed in human studies on oral health. Biological sex influences oral disease susceptibility through hormonal, immunological, and microbiome-related mechanisms. Concomitantly, gender as a social construct modulates health through psychosocial stress, health care access, and societal norms. Sexuality intersects with oral health through behavioral risks, stigma, and discrimination, especially among lesbian, gay, bisexual, transgender, and queer or questioning populations. Despite their importance, oral health research often treats sex as a binary demographic variable, excluding sexual and gender minority individuals. There is a lack of meaningful integration of these variables across all phases of research, from proposal development and data collection to analysis and knowledge creation. This results in limited generalizability, perpetuates health inequities, and impedes the development of inclusive, evidence-based, and person-centered interventions. Furthermore, dental education and research training programs often lack comprehensive content on sex, gender, and sexuality, contributing to research approaches and training that reinforce binary-centered investigations. Substantial gaps in mentorship, representation, and inclusive curricula largely contribute to the underrepresentation of gender-diverse scholars and leaders in oral health. To address these gaps, a multipronged action plan is necessary, including an inclusive research design, robust data collection tools, curriculum reform that integrates person-centered frameworks, community engagement and service-learning, policy change, and accountability mechanisms. The integration of intersectionality, pertinent sex, gender, sexuality, and social determinants of health in oral health research and education is essential for achieving scientific rigor, health equity, and culturally responsive care for all populations.

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)0.143
metaresearch head score (Gemma)0.172
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.857
Threshold uncertainty score0.754

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1430.172
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.008
Science and technology studies0.0050.013
Scholarly communication0.0100.021
Open science0.0020.009
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0110.002

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 head0.496
GPT teacher head0.641
Teacher spread0.145 · 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.

Study designNot applicable
DomainMethods
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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