Factors influencing attrition of students in a baccalaureate nursing program
Bibliographic record
Abstract
A nursing shortage is looming in Canada (Canadian Nurses Association, 1997, November 4). It is \ninperative that as many students graduate from nursing school as possible in order to alleviate this \nproblem. This purpose o f this study was to discover the reasons for student attrition in a \nCanadian Baccalaureate School of Nursing. Tinto?s model o f college student attrition was \napplied as the conceptual framework. A Nursing Student Attrition Survey was completed by \nforty student persisters and nineteen student leavers. Comparisons between the two samples \nrevealed significant differences in that older students, students from urban areas, and students \nwhose mothers and fathers had less post-secondary education were more likely to leave the \nprogram of study prior to graduation. The same was found true for students with lower level \nintentions, goal and institutional commitment, and students with more external commitments. \nStudents persisters were found to feel better about their academic performance and felt that they \nhad more positive peer group interactions than did the student leavers.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".