Creating my academic self and space: autoethnographic reflections on transcending barriers in higher education
Bibliographic record
Abstract
This article focuses on my ethnographic self-reconstruction in order to explore my academic journey, by critically evaluating the influence of professional academic cultures on my teaching practice, with a view to understanding my professional identity. I make visible to the reader and myself my suppressed feelings, emotions and ambitions by analysing learning opportunities that facilitate my ‘being’ an academic. Drawing on theoretical frames from autoethnography, I engage in personal epistemological vigilance by directing my sociological gaze inwards. I retroactively and selectively draw on diary recordings of my own micro-ethnographies, and my teaching portfolio statement as the data sets. My entry into this slippery, treacherous space evokes feelings of vulnerability and hyper-visibility. It illuminates the struggle of being on the right-hand side of binaries such as disciplinary specialist/ interdisciplinary researcher, experienced/novice academic, and scholar/teacher. This work has implications for other academics who feel undervalued, over-extended and trapped in the labour of teaching.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".