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Record W7117690152 · doi:10.1136/bmjopen-2025-104975

Ethnological study of birth timing decisions: a scoping review protocol

2025· article· en· W7117690152 on OpenAlexaff
Yagana Samim, Nicholas D. Spence

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProtocol (science)Public healthHealth services researchMEDLINEOpen scienceEpidemiology

Abstract

fetched live from OpenAlex

Introduction Birth timing decisions, a type of reproductive decision-making (RDM), have yet to be explored in the RDM literature through an ethnological lens. Existing literature has generally observed reproductive decisions across broad racial categories, which has not allowed for a nuanced understanding of the cultural factors influencing birth timing decisions. This scoping review aims to answer the following questions: (1) How do different ethnic groups approach birth timing decisions? (1a) What social and structural factors influence birth timing/spacing decisions for different ethnic groups? (1b) What cultural logics emerge during these decision-making processes? Specifically, these questions are explored within the geographical context of the USA, as its diverse demographics, size and availability of data make it an ideal case. This scoping review thus makes two key contributions to the health literature: (1) it explores trends in birth timing decisions, which is a type of RDM that has typically been overlooked in favour of topics such as birth control use and timing, abortions and miscarriages, and wrongful births, and (2) it explores birth timing decisions from an ethnological perspective in a highly relevant context, expanding beyond homogenising race-based categorisations, toward a nuanced understanding of cultural considerations in family planning decisions across the USA. Methods and analysis This scoping review follows the protocol laid out in the extension of the Preferred Reporting Items for Systematic Reviews and Meta-analysis, for scoping reviews and will use thematic analysis[1]. Using four databases, Medline, Web of Science, the International Bibliography of the Social Sciences and Sociological Abstracts, original research articles have been captured using the attached search strategy, which contains key terms related to both the independent and dependent variables of interest. Results have been filtered to include only studies published in English within the last 20 years (2005 to present) and conducted in the USA. These criteria were implemented using a verified search string. Additional filters for human-only results were applied to the Medline search. All relevant publications have been imported to Covidence, where the authors will independently conduct title/abstract screening and full-text screening, as well as a thematic analysis of the extracted data from the remaining articles that meet the inclusion criteria. The authors aim to organise and synthesise all findings using the attached data extraction table (see supplemental documents). Ethics and dissemination This study uses existing publications and therefore does not require ethics submission or review. We intend to publish our scoping review in a peer-reviewed journal. Trial registration number This scoping review protocol has been registered via Open Science Framework (OSF); the preregistration can be found at the following link: https://osf.io/6f4bq

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)0.164
metaresearch head score (Gemma)0.154
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.164
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1640.154
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0110.009
Bibliometrics0.0270.022
Science and technology studies0.0060.007
Scholarly communication0.0090.009
Open science0.0070.008
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0810.014

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 head0.397
GPT teacher head0.612
Teacher spread0.215 · 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
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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