‘Expressing inner dialogues of teaching experience: Writing as a path to emancipation and growth’
Bibliographic record
Abstract
This paper explores the complexities and personal demands of entrepreneurship education (EE) teaching, emphasising the importance of writing about teaching experiences as a tool for self-exploration and professional development. Using Collaborative Auto-Ethnography (CAE), this study builds on 18 months of collaborative work, designing and delivering three Professional Development Workshops (PDWs) for entrepreneurship educators. These workshops provided inclusive spaces for educators to share, reflect, and connect with their professional identities. By centring personal narrative, this paper challenges conventional pedagogical norms and fosters self-reflective teaching practices. By drawing on the positionality of our conversations, experiences, and intellectual growth, we offer educators and scholars a processual approach to writing about their teaching experiences. This practice amplifies diverse experiences and pedagogies, contributing to a more equitable and authentic educational landscape in entrepreneurship education.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.034 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| 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".