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Record W1973436711 · doi:10.1177/0741713605286174

Market Socialism Meets the Lost Generation: Motivational Orientations of Adult Learners in Shanghai

2006· article· en· W1973436711 on OpenAlexaff
Roger Boshier, Yan Huang, Qihui Song, Lei Song

Bibliographic record

VenueAdult Education Quarterly · 2006
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocialismAdult educationPsychologyChinaSubjectivityPoliticsGender studiesSocial psychologyPostmodernismSocial changeSociologyDevelopmental psychologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

In Western countries, women and men, young and old, enroll in adult education for different reasons. This is even more the case in China. This study helps Shanghai program planners better appreciate learners by understandinghow motivational orientations vary as a function of gender and age. The Chinese version of the Education Participation Scale was administered to 448 adults enrolled in Shanghai adult education classes. It had a factor structure loosely comparable to the English version. Women were more inclined than men to be enrolled for social stimulation, social contact and cognitive interest. However, gender differences were less pronounced than those for age. The Cultural Revolution and pressures of market socialism in postmodern Shanghai appeared to shape motivational orientations of participants who came of age between 1966 and 1976. Just the fact that learners were asked about motivational orientations may change the politics of human subjectivity in Shanghai adult education.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.308
Teacher spread0.294 · 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

Citations22
Published2006
Admission routes1
Has abstractyes

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