Bibliographic record
Abstract
A single case study of a student was elaborated upon to illustrate the process of change through education. By choosing to study a graduate who had minimal background preparation and minimal interest in entrepreneurship before the education programme, the researchers have attempted to address some of the limits of change possible through entrepreneurship education. A structured interview was used to provide the initial ‘before and after’ account, after which extended and repeated probing was employed as the primary tool for exploring the personal development process involved. The case history was then used as a basis for developing a model of personal development required to make the transition from non-entrepreneur to entrepreneur. This case study was further intended to illustrate some of the relative merits of conducting in-depth case analysis over survey research in the domain of entrepreneurship education. Without in-depth case studies of individuals it is hard to know how much entrepreneurship programmes can change individuals. The possibility remains that entrepreneurship programmes just take potential entrepreneurs and give them a few more tools. Case studies of the change process can provide educators with a more complete understanding not only of what changes are possible within the confines of an education programme, but also of what programme interventions are more likely to produce the desired changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".