PARENTAL AND SOCIAL FACTORS PREDICT THRIVING DURING THE TRANSITION TO UNIVERSITY
Bibliographic record
Abstract
This study investigated, through an attachment theoretical lens, the relationship between first-year university students’ personal and academic adjustment and 3 psychosocial resources: parental attachment, student resources (parental support, social support, ways of reducing loneliness, emotion regulation, coping strategies, locus of control), and gender. Participants answered questionnaires relating to their psychosocial resources and post-secondary adjustment in first and second term. These data were analysed using a planned regression analysis. In Term 1, paternal attachment predicted students’ emotional adjustment, with social and personal resources accounting for this relationship, and was related to academic adjustment via locus of control. Maternal attachment predicted academic adjustment. Gender and locus of control predicted academic performance (as measured by grade point average [GPA]). In Term 2, parental attachment predicted emotional adjustment, with social support accounting for this relationship, but academic adjustment was no longer related to paternal attachment. Overall, gender and locus of control predicted academic success. Suggestions are made for developing transitional theoretical models that address psychosocial processes that will help shape responsive institutional programming and planning in support of incoming college students. These recommendations include designing more personalized programs to match students and their family systems where possible and keeping parents/guardians informed of helpful supports for students’ experiences when needed.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".