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Record W1743966677 · doi:10.3233/wor-141958

Midlife mothers favor `being with' children over work and careers

2015· article· en· W1743966677 on OpenAlexaboutno aff
Patricia Morgan, Joy Merrell, Dorothy Rentschler

Bibliographic record

VenueWork · 2015
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
FundersUniversity of New EnglandSwansea University
KeywordsPerceptionPsychologyContext (archaeology)Work (physics)Developmental psychologyHealth careGender studiesNursingSociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The majority of American women juggle careers and the demands of mothering. The experiences of midlife mothers on the issues of work and motherhood are important to explore because birth rates for older women continue to rise in the United States and in other countries including the U.K. and Canada. OBJECTIVE: To present a unique viewpoint on work and mothering from the perspectives and experiences of older first-time mothers. METHODS: A purposive sample of thirteen women aged 45-56 years old participated in two in-depth interviews. Findings emerged in the context of a larger hermeneutic phenomenological study that aimed to understand older first-time mothers' perceptions of health and mothering during the transition to menopause. RESULTS: A paradox emerged in which the realities of motherhood did not meet the women's expectations. They were surprised by the centrality of commitment they felt towards the child and voiced strong ideals about how to do mothering right that included making changes to work schedules to be more available to their children. CONCLUSION: Health care professionals should be aware of specific issues that exist for older first-time mothers including adjustments to work. This knowledge will inform the support, education and care provided for these women.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.045
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.025
GPT teacher head0.299
Teacher spread0.273 · 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
Published2015
Admission routes1
Has abstractyes

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