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Record W2294618447 · doi:10.1080/19496591.2016.1110036

Predictors of Academic Procrastination in Asian International College Students

2016· article· en· W2294618447 on OpenAlexaff
Robert Jay Lowinger, Ben C. H. Kuo, Hyun-a Song, Lakshmi Mahadevan, Eunyoung Kim, Kelly Yu‐Hsin Liao, Catherine Y. Chang, Kyong‐Ah Kwon, Suejung Han

Bibliographic record

VenueJournal of Student Affairs Research and Practice · 2016
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsProcrastinationPsychologyCoping (psychology)AcculturationLogistic regressionStudent affairsLanguage proficiencySocial psychologyHigher educationGraduate studentsClinical psychologyMedical educationPedagogyEthnic groupMedicineSociology

Abstract

fetched live from OpenAlex

This study examined the relationships among acculturative stress, coping styles, self-efficacy, English language proficiency, and various demographic characteristics as predictors of procrastination behavior in Asian International students (N = 255) studying in the United States. Results of multiple logistic regression indicated that a collective coping style, avoidant coping style, academic self-efficacy, and English language proficiency were the significant predictors of academic procrastination in non-Indian Asian international students. Implications for college student affairs professionals and researchers are addressed.

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)0.007
metaresearch head score (Gemma)0.005
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 score0.063
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.075
GPT teacher head0.477
Teacher spread0.402 · 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

Citations45
Published2016
Admission routes1
Has abstractyes

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