Paying the piper: the costs and consequences of academic advancement
Bibliographic record
Abstract
In many professions there are qualifications to gain and professional standards to achieve. Lawyers pass the bar and doctors pass their boards. In academic life the equivalent is a doctorate, closely followed by a profile of peer-reviewed publication. To hold a doctoral degree is the common requirement to become ‘academic’ but does it prepare individuals to advance in an academic career? In choosing the idiom ‘paying the piper’ (i.e. where one must pay the costs and accept the consequences of one's actions) we recognise that in seeking to develop our scholarly profiles we had to choose to adapt successfully to global workplace expectations, modify our professional aspirations or refuse to participate. In this paper we examine the challenges we faced as academics in physical education as we progressed from beginning to mid-career stages. We focus particularly on challenges related to seeking external research funding, exploring our assumptions about academic life and the perceived expectations that lie under the surface around research funding, teaching and service. Through the use of self-study we demonstrate how our perceptions of academic career progress meant paying personal and professional costs that we were largely (and perhaps naively) unaware of when we entered the academic workforce. Data consisted of Ashley’s reflective diaries generated over the past six years, which were analysed deductively based on an understanding of salient experiences of academic life, most notably, those related to the pursuit of funding and its relationship to academic advancement. Tim played the role of critical friend by asking probing questions, relating personal experiences to instances in Ashley's data, and offering alternative interpretations of Ashley's insights. By sharing our experiences we hope early career academics (ECAs) may relate to and learn from our naivety. In this way, there may be implications for the induction and mentoring of future ECAs.
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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 | 0.014 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".