Conceptualizing Thriving in Graduate Students: A Self-Determination Theory and Well-Being Perspective
Bibliographic record
Abstract
The purpose of this mixed methods study is to investigate and understand how the notion of student thriving can be conceptualized and understood within the context of post-secondary graduate studies. While existing research on human thriving provides insight into how the notion can be conceptualized and understood across the lifespan, student thriving within institutions of higher learning has been largely overlooked. Prior to this study, little research had attempted to understand and address the notion of student thriving at the post-secondary level with the graduate student experience remaining largely untouched in the literature. This research is not only foundational in understanding and conceptualizing student thriving among graduate students, but also provides a foundation upon which further research can be developed. In addition, the six overarching themes—Being, Connecting, Engaging, Achieving, Enjoying, and Balancing—provides the beginning groundwork for understanding the graduate student experience, and how programs and institutions can best support those enrolled within their graduate programs.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.005 |
| 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".