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Record W2071768586 · doi:10.1353/cja.2006.0015

Double-Duty Caregiving: Women in the Health Professions

2005· article· en· W2071768586 on OpenAlexaff
Catherine Ward‐Griffin, Judith Belle Brown, Anthony A. Vandervoort, Susan M McNair, Ian Dashnay

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsWestern University
Fundersnot available
KeywordsFeelingDutyMental healthNarrativeNursingNegotiationIsolation (microbiology)PsychologyHealth careMedicineSocial psychologySociologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT The purpose of this feminist narrative study was to examine the experiences of women in four different health professions (nursing, medicine, physiotherapy, and social work) who provided care to elderly relatives. Although caring is a central and common feature of the personal and professional lives of many women (Baines, Evans, & Neysmith, 1991; Baines, 2004), the separation of professional, paid caregiving from family, unpaid caregiving among health care providers is problematic. Study findings suggest that female health professionals who assume familial responsibilities continually negotiate the boundaries between their professional and personal caring work. Despite the use of a variety of strategies for managing their double-duty caregiving demands, many women experienced a dramatic blurring or erosion of these boundaries, resulting in feelings of isolation, tension, and extreme physical and mental exhaustion. These findings suggest that women who are double-duty caregivers, especially those with limited time, finances, or other tangible supports, may experience poor health, which warrants further study.

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)0.003
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.008
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.282
Teacher spread0.256 · 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
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

Citations61
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicWork-Family Balance ChallengesFrench-language works237,207