Bibliographic record
Abstract
This paper is based upon a conceptual approach to making a scholarly addition to the privileged academic discourse. This paper develops the methodology of a subjective academic narrative to address the issue of academic collegiality that is being explored. This methodology involves a journey of intellectual enquiry into the work of the self as data. This subjective academic narrative is a response to the research question: 'in today's world of the subjective self and online interactions is collegiality possible or even desirable?'. The conceptual approach of this paper involves constructing a personal narrative arising from experience and reviewing academic literature regarding the possibly inherent discordance between collegiality and personal career development. The core business of the university may well be teaching undergraduate students, as this brings in the most sure and significant income, but if you want to get up the academic scale, you must also excel at the various demands of the promotions regulations. These involve proof of collegiality as well as personal aspects of teaching and learning, research, and management of courses, people and discipline areas. This paper explores whether or not such interactions are possible.
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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 | 0.026 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.010 | 0.039 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| 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".