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Record W2783737332

Parents’ Experience Caring for Young Children with Minor Illness: An Ecological Perspective

2009· article· en· W2783737332 on OpenAlexaffvenue
Joan Turner, Carmel French

Bibliographic record

VenueJournal of Childhood Studies · 2009
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsPerspective (graphical)Minor (academic)PsychologyDevelopmental psychologyEcologyBiologyHumanitiesPhilosophyArt
DOInot available

Abstract

fetched live from OpenAlex

Typical family routines break down when a child is ill. For working par-ents, child care and employment con-ditions and demands inevitably play a role in the process of determining short-term child care arrangements. According to previous research, the decision to stay home and care for the ill child is complex (Polyzoi & Babb, 2004: Polyzoi, Elfenbaum, & Babb, 2006). The aim of this current study is to gain insight into the perspective of working parents as they balance child care, family and work during episodes of minor illness in children. Personal experiences of eight mothers were assessed through semi-structured interviews. The analysis focuses on the interrelationships between the contexts of daily family living, as guided by Ecological theory (Bronfenbrenner, 1979). The descrip-tions of experiences and events sur-rounding episodes of childhood ill-ness make reference to home, the child care setting and the workplace, reflecting the attitudes and values of the larger society. The statement of one mother, “You know they don’t want you to send your children, but yet they’re not helping you stay home.” reflects the overall sense of stress experienced by families as they deal with these occurrences.

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)0.002
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.078
GPT teacher head0.446
Teacher spread0.368 · 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

Citations1
Published2009
Admission routes2
Has abstractno

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