The Role of Individual Absorptive Capacity, Subjective-Wellbeing and Cultural Fit in Predicting International Student’s Academic Achievement and Novelty in China
Bibliographic record
Abstract
This study investigated the role of cognitive-(absorptive capacity), psychological-(subjective-wellbeing) and cultural-fit-factors as predictors of academic achievement-novelty in a Chinese-C9-league-University. We addressed the question of what drive student’s achievement of high graduations requirements and innovativeness in their Host-University; focusing mainly on whether interactionistic-nature-(fit-capabilities) are better mechanisms. The quantitative approach was adopted; collect 234 valid data via survey questionnaire, and conduct analysis via structural equation modeling technique. We found that individual-absorptive-capacity has significant effect on supervisor-fit, but a non-significant effect on university-fit dimensions of cultural-fit. Subjective-wellbeing significantly affects both dimensions of cultural-fit. The findings further show how supervisor-fit and university-fit indirectly mediate the (absorptive-capacity, subjective-wellbeing)-achievement-novelty relationship. We highlight the importance of cultural-diversity-awareness; considering supervisor-institutional-fit-factors in research-mentorship-development to support international-students ‘induction for research productivity in educational-settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".