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Record W2316284822 · doi:10.1332/204674312x656284

Trying to do more with less? Negotiating intensive mothering and financial strain in Canada

2012· article· en· W2316284822 on OpenAlexafffundabout
Jeanna Parsons Leigh, Shelley Pacholok, Tara Dawn Snape, Anne H. Gauthier

Bibliographic record

VenueFamilies Relationships and Societies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsOkanagan University CollegeUniversity of British ColumbiaSimon Fraser UniversityUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNegotiationConstruct (python library)PoliticsHegemonyWork (physics)SociologyPolitical scienceGender studiesSocial scienceLaw

Abstract

fetched live from OpenAlex

This article explores the ways in which middle-income mothers negotiate the hegemony of intensive mothering when faced with financial strain. We consider how finances are linked to mothers’ ability to practise their preferred version of ‘good’ mothering, and the strategies used to marshal the financial resources necessary to implement this model. We find that much heterogeneity exists in the ways that mothers respond to the discourse of intensive mothering, and that financial resources are linked to how mothers both construct and practise ‘good’ mothering. For example, in an effort to reconcile tensions between their constructions of ‘good’ mothering and paid labour, they employ strategies such as remaining the primary caregiver for their children while also working at night, taking on contract work and taking in boarders. This research has specific implications for the ways that middle-income families are functioning in the current neoliberal political and economic climate.

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 score0.496
Threshold uncertainty score0.757

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 studies0.0010.000
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 head0.036
GPT teacher head0.258
Teacher spread0.222 · 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

Citations24
Published2012
Admission routes3
Has abstractyes

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