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Record W2334390592 · doi:10.1017/s0144686x11000419

Baby-boomers and the ‘denaturalisation’ of care-giving in Quebec

2011· article· en· W2334390592 on OpenAlexaffabout
Nancy Guberman, Jean‐Pierre Lavoie, Ignace Olazabal

Bibliographic record

VenueAgeing and Society · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsBaby boomersWifeRealmCare workPsychologyQualitative researchSociologyGender studiesWork (physics)Public relationsPolitical scienceNursingMedicineLaw

Abstract

fetched live from OpenAlex

ABSTRACT The North American post-war generation, known as the baby-boomers, has challenged traditional family relations and the sexual division of labour. How do these challenges play out in the face of frail, ill or disabled family members? A study undertaken in Montreal, Quebec, with baby-boomer care-givers aimed to raise understanding of the realities of this group. We met with 40 care-givers for a one and a half-hour qualitative interview to discuss their identification with their social generation, their relationship to care-giving, their values regarding care-giving, and the reality of the care-giving they offer. The findings indicate that women, in particular, no longer identify themselves mainly in terms of family. For most, care-giving is not their only or even their dominant identity. They are actively trying to maintain multiple identities: worker, wife, mother, friend and social activist, alongside that of care-giver. They are also participating in the very North American process of individualisation, leading to what we call the ‘denaturalisation’ of care-giving. Notably, the women we met with call themselves ‘care-givers’ and not simply wives, daughters or mothers, denoting that the work of care-giving no longer falls within the realm of ‘normal’ family responsibilities. These care-givers thus set limits to their caring commitments and have high expectations as to services and public support, while still adhering to norms of family responsibility for care-giving.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.263
Teacher spread0.243 · 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 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

Citations14
Published2011
Admission routes2
Has abstractyes

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