‘Swallow your pride and fear’: the educational strategies of high-achieving non-traditional university students
Bibliographic record
Abstract
With more graduates, degree outcomes have a renewed significance for high-achieving students to stand out in a graduate crowd. In the United Kingdom, over a quarter of undergraduates now leave university with the highest grade – a ‘first-class’ degree – although students from non-traditional and underprivileged backgrounds are the least likely. This article explores the experiences of high-achieving non-traditional (HANT) university students. Drawing on in-depth interviews with 30 final-year students who are on course to achieve a first-class degree from working-class, minority ethnic and/or mature backgrounds, we examine their pathways to academic success through identity works and negotiations. We argue that early successes are crucial for students to re-evaluate their self-expectations as students who can achieve in higher education, while self-esteem, pride or fear can prevent students from maximising their available resources and opportunities. Implications for practice and policy are discussed, including the reflective advice from HANT students towards academic success.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.030 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".