Bibliographic record
Abstract
Drawing on 24 semi-structured interviews, this small-scale qualitative study delves into mature students’ social, academic, and career preparation experiences pursuing college education. Using Schlossberg’s (1989) transition model, the findings reveal that mature students’ overall experience is influenced by their mature status, as they possess greater confidence derived from their previouswork and education experiences and the acquisition of new skills from their programs. However, some mature students perceive the career services offered by the college as being geared toward younger students, often disregarding their previous work experience. Consequently, they find these services less applicable to their needs. The transitioning-in stage for mature students is characterized by initial uncertainty that gradually transforms into a growing sense of confidence, fuelled by their experiences. These experiences motivate mature students to actively contribute to the college community by becoming mentors and assuming a supportive role for younger students during the transition-through stage. The transitioning-out for mature students involves evaluating career options and harbouring some skepticism. Nonetheless, the majority of participants expressed positive experiences and excitement about the new chapters in their lives. This study highlights the significance of tailored support and resources that acknowledge the specific needs and experiences of mature students throughout their college education.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".