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Record W4386390999 · doi:10.1177/00220221231195930

Social Mobility and Motivational Payoff: Achievement Motivation Is More Important in Students’ Performance and Well-Being in Cultures With High Versus Low Social Mobility

2023· article· en· W4386390999 on OpenAlexaff
Nigel Mantou Lou, Liman Man Wai Li

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychologyFear of failureNeed for achievementSocial psychologyGoal theoryCompetence (human resources)Academic achievementGoal orientationSocial mobilityMultilevel modelSet (abstract data type)Test (biology)Developmental psychologySociology

Abstract

fetched live from OpenAlex

Achievement motivation encompasses a well-establish distinction between the motive to avoid failure (e.g., fear of failure) and the orientation to improve competence (e.g., mastery goal). But how well do they generalize across cultures in understanding students’ performance and well-being? We argue that students’ achievement motivation is less pronounced in societies characterized by low (vs. high) social mobility, where people have fewer opportunities to change their social status. To test this hypothesis, we analyzed a cross-national data set ( n = 498,362 high-school students from 65 regions) using multilevel modeling. The results indicated that societal-level social mobility significantly moderated the role of (a) mastery goals and fear of failure on academic performance and (b) fear of failure on well-being. These associations were stronger in societies with high (vs. low) social mobility, suggesting that students derive greater academic benefits from mastery goals and fear of failure in societies with higher social mobility. In such societies, however, fear of failure also poses a stronger hindrance to students’ well-being. These findings highlight that the same type of motivation may operate differently across cultures and that socioecological environments may influence the motivational impacts on learning and well-being.

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)0.001
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 score0.030
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.432
Teacher spread0.396 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

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