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Record W3154599345 · doi:10.1080/02646838.2021.1892044

The role of motherhood schemas and life transitions in reproductive intention formation

2021· article· en· W3154599345 on OpenAlexafffund
Shaneice Fletcher-Hildebrand, Karen Lawson, Pamela Downe, Mel Bayly

Bibliographic record

VenueJournal of Reproductive and Infant Psychology · 2021
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFertilityPsychologySocial psychologyCognitionDevelopmental psychologySociologyDemographyPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: This study provides a theory-based snapshot of the processes involved in women's fertility intention formation and decisions regarding the timing of motherhood. BACKGROUND: The trend to defer childbearing is linked with both empowering and challenging outcomes for women. The cognitive-social (C-S) model suggests that deliberative thinking regarding reproduction occurs following fertility-relevant life transitions, which results in fluctuations in motherhood schemas and fertility intentions. This framework was applied to explore fertility intention formation. METHODS: Semi-structured interviews were conducted with twelve women who either had children or desired children. RESULTS: Two overarching themes central to the C-S model are discussed: (a) passive expectations and (b) deliberative intentions. Women's motherhood schemas were often underpinned by schematic structures (e.g. group norms and scripts) and material structures (e.g. observational influences). Life transitions and personal experiences tended to prompt deliberative thinking about motherhood plans. CONCLUSION: The results were generally consistent with the C-S model, but highlight complexities to consider when investigating fertility expectations and intentions.

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)0.002
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 score0.528
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.021
GPT teacher head0.329
Teacher spread0.308 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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