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Record W2566367949 · doi:10.2147/ijwh.s119757

Searching for sex- and gender-sensitive tuberculosis research in public health: finding a needle in a haystack

2016· article· en· W2566367949 on OpenAlexaff
Bilkis Vissandjée, A Mourid, Christina Greenaway, Wendy E Short, Jodi. A. Proctor

Bibliographic record

VenueInternational Journal of Women s Health · 2016
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsMcGill UniversityJewish General HospitalUniversité de Montréal
FundersShastri Indo-Canadian Institute
KeywordsPublic healthTerminologySocial mediaLibrary scienceSociologySocial sciencePublic relationsMedicinePolitical scienceNursingComputer science

Abstract

fetched live from OpenAlex

Despite broadening consideration of sex- and gender-based issues in health research, when seeking information on how sex and gender contribute to disease contexts for specific health or public health topics, a lack of consistent or systematic use of terminology in health literature means that it remains difficult to identify research with a sex or gender focus. These inconsistencies are driven, in part, by the complexity and terminological inflexibility of the indexing systems for gender- and sex-related terms in public health databases. Compounding the issue are authors' diverse vocabularies, and in some cases lack of accuracy in defining and using fundamental sex-gender terms in writing, and when establishing keyword lists and search criteria. Considering the specific case of the tuberculosis (TB) prevention and management literature, an analysis of sex and gender sensitivity in three health databases was performed. While there is an expanding literature exploring the roles of both sex and gender in the trajectory and lived experience of TB, we demonstrate the potential to miss relevant research when attempting to retrieve literature using only the search criteria currently available. We, therefore, argue that for good clinical practice to be achieved; there is a need for both public health researchers and users to be better educated in appropriate usage of the terminology associated with sex and gender. In addition, public health database indexers ought to accept the task of developing and implementing adequate definitions of sex and gender terms so as to facilitate access to sex- and gender-related research. These twin advances will allow clinicians to more readily recognize and access knowledge pertaining to systems of redress that respond to gendered risks that compound existing health inequalities in disease management and control, particularly when dealing with already complex diseases. Given the methodological and linguistic challenges presented by the multidimensional and highly contextual nature of definitions of sex and gender, it will be important that this review task be undertaken using a multidisciplinary approach.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.383
GPT teacher head0.504
Teacher spread0.121 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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