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Record W4214865907 · doi:10.1177/14661381211054027

Toward a non-individualistic analysis of neoliberalism: the stay-fit maternity trend in Taiwan

2022· article· en· W4214865907 on OpenAlexafffund
Amélie Keyser-Verreault

Bibliographic record

VenueEthnography · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNeoliberalism (international relations)IndividualismSociologyGender studiesPolitical economySocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

This paper explores the new sexy maternity phenomenon in Taiwan's neoliberal context, focusing on analyzing mothers' intense pursuit of getting their bodies back into shape. More specifically, I problematize and nuance the taken-for-granted individualistic analyses of neoliberalism and illustrate how getting the body back into shape involves multiple social actors, a consequence of women's relational self. Not only does women's beauty give face to their spouses and honor the family, but consideration of social effects are decisive factors in women's beautification of their bodies. Thus, I emphasize that the material or immaterial profit of agentic individualism can be collective. In this context, an individual's entrepreneurial activity should not necessarily be interpreted as an abnegation of the social, since tactful management of social relationships is an indispensable immaterial labor of women's aesthetic entrepreneurship. I propose the theoretical frame of "reconstruction of the relationality" to better understand the trans-individual relationship under neoliberalism.

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)0.001
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.083
GPT teacher head0.341
Teacher spread0.258 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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