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Record W4319316477 · doi:10.1111/fare.12812

Intensive mothering and informational habitus: Interplays in virtual communities

2023· article· en· W4319316477 on OpenAlexafffund
Maryline Vivion, Benjamin Malo

Bibliographic record

VenueFamily Relations · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsCentre hospitalier de l'Université LavalUniversité LavalInstitut National de Santé Publique du Québec
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHabitusReflexivityContext (archaeology)IdeologyExperiential learningEthnographyExperiential knowledgePsychologySociologySocial psychologyDevelopmental psychologyPedagogyEpistemologySocial science

Abstract

fetched live from OpenAlex

Abstract Objective This study aimed to explore how virtual communities of mothers shape the informational habitus in the context of the intensive mothering ideology. Background Mothers' involvement and dedication are perceived as essential to children's development. Some mothers join virtual communities for health information to ensure that they are doing the best for their child. Method An online ethnography in three virtual communities of mothers was conducted, in addition to individual interviews with 16 mothers of young children (18 months and below). Results Mothers use virtual communities for emotional and informational support. Experiential knowledge and referenced information are highly valuable. Furthermore, mothers are reflexive and choose what information they integrate based on their educational capital and their personal skills. Finally, choice appeared to be the practical operator of the informational habitus. Conclusion Our results suggest that the sense of belonging developed in virtual communities shapes a new informational habitus based on the importance of being an informed mother. Implications Mothers want to make the best possible decisions for their child's health. To do so, they deploy reflexive practices to process information. This suggests that other than their physicians, they also trust an important array of sources of information.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.512

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 studies0.0000.000
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 head0.046
GPT teacher head0.322
Teacher spread0.277 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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