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Record W4205370465 · doi:10.1080/18692729.2021.2022572

Autonomy and responsibility: Women’s life and career choices in urban Japan

2022· article· en· W4205370465 on OpenAlexfundno aff
Vincent Mirza

Bibliographic record

VenueContemporary Japan · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAutonomyArticulation (sociology)Context (archaeology)Moral responsibilityWork (physics)ImpossibilityPoliticsSociologyFreedom of choiceReproductionPolitical economyGender studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

Based on fieldwork and interviews collected over the past decade, this article examines how young single women in Tokyo are trying to make choices for their careers, navigating between the political economy of labour and reproduction. The article looks at how these women make choices within an ever-changing context where the Japanese moral economy of the postwar coexists with a neoliberal articulation of individual responsibility for life choices. Their experiences reveal the important contradictions between the conservative work regime within companies and the flexible job market they have created. This creates impossible contradictions that place women in both a precarious job market, and when they work in more stable conditions, results in the impossibility of having a family. This article will discuss how, despite these contradictions, young women create meaningful work while attempting to find freedom of choice as they try to define work and life choices not only as a social and moral responsibility, but also as an individual choice. In other words, I seek to show how life choices articulated during the post-growth era are creating new configurations and new challenges within the context of Japan’s ongoing economic and demographic challenges.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.056
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.277
Teacher spread0.235 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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