MétaCan
Menu
Back to cohort
Record W2775095831 · doi:10.1186/s12978-017-0423-1

Exclusion of married adolescents in a study of gestational diabetes mellitus: a case study

2017· article· en· W2775095831 on OpenAlexfundno aff
Mala Ramanathan, K Sakeena

Bibliographic record

VenueReproductive Health · 2017
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
FundersDalhousie UniversityUniversity of Oxford
KeywordsReproductive medicineConfidentialityGestational diabetesMedicineInclusion and exclusion criteriaDiabetes mellitusInformed consentInclusion (mineral)Marital statusDemographyFamily medicinePsychologyPregnancyGerontologyPopulationLawEnvironmental healthSocial psychologySociologyAlternative medicinePolitical scienceGestation

Abstract

fetched live from OpenAlex

A study on gestational diabetes mellitus (GDM) among 200 married women in Malappruam, Kerala, India, chose to exclude married women below the age of 18 from participation. Marriages before age 18 are not considered legally valid and persons below age 18 do not have the status of an adult. Parents are considered the legal guardians of married women under age 18, but because marriages are patrilocal, obtaining consent from parents would have time costs. Further, obtaining parental consent may also be considered disrespectful of the in-laws. The inclusion of married adolescents in this study was considered difficult for these reasons. This exclusion can also result in wrongly estimating the levels of GDM among all women at risk. We argue that such exclusion is also unethical; it unfair to exclude women who stand to benefit from participation by enabling them to identify the enhanced life time risk for diabetes mellitus and monitor their future health status better. Recognizing married adolescents as emancipated minors would enable their participating without violating confidentiality regarding their GDM status to parents and in-laws.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.403
Teacher spread0.344 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueReproductive HealthSame topicGestational Diabetes Research and ManagementFrench-language works237,207