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Record W6977930950 · doi:10.7939/r34m22

Daughters of mothers with Multiple Sclerosis: their experiences of play

2010· dissertation· en· W6977930950 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2010
Typedissertation
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingMaturity (psychological)Focus groupPhenomenology (philosophy)Interpretative phenomenological analysisLived experienceFocus (optics)

Abstract

fetched live from OpenAlex

This study described the play experiences of daughters who were caregivers to their mothers with multiple sclerosis (MS). The experiences of four Canadian-Caucasian women aged 19-26 were captured using phenomenological methods of individual and focus group interviews, field notes, and artefacts. Three themes with supporting sub-themes emerged: (a) being a good daughter, (b) blurred relationship boundaries, and (c) encumbered play. Caregiving for their mothers was part of being a good daughter. Excessive caring duties changed their roles from being daughters to caregivers and contributed to feelings of maturity over peers. Their mother-daughter relationship boundaries were blurred and the participants wished to spend more time as daughters. Play, although sometimes limited, was highly valued and provided an escape from caregiving. Using family systems theory to interpret the findings, it was concluded that support for families living with MS would release children from caregiving duties so rounded childhood play could be experienced.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.013
GPT teacher head0.204
Teacher spread0.192 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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