What Helps and Hinders the Hopefulness of Post-Secondary Students Who Have Experienced Significant Barriers
Bibliographic record
Abstract
This study investigated how undergraduate students in Canada and the United States experience high levels of hope in the face of challenges, specifically, what helps and hinders their hopefulness. Enhanced Critical Incident Technique was used, consisting of in-depth, semi-structured interviews allowing for open-ended, clarifying questions. Fifteen students self-reporting high levels of both hope and barriers were interviewed to ascertain their definitions of hope and the factors that helped and hindered hopefulness. Participants defined hope as a multidimensional concept involving affective, cognitive, behavioural, affiliative, contextual and temporal factors. 281 incidents revealed internal and environmental factors that influenced hope. Internal factors included future goals, attitude, passion, self-efficacy, social and professional contribution, refocusing activities, negative emotions and cognitions, and health. Environmental factors included support, role models, possibilities and opportunities, school, negative/ unsupportive people, situations outside one’s control, and economic/financial challenges. Spirituality emerged as an internal and environmental factor. Relationships emerged as having the most significant positive and negative impact on hope. Findings suggest that hope and the factors influencing it can play an integral role in students’ personal and career development, and that there is need for career counsellors in post-secondary Career Services departments.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".