Constituting the Academic Performer: The Spectre of Superficiality and Stagnation in Academia
Bibliographic record
Abstract
Journal rankings and performance measurement schemes tend to become increasingly influential within many fields of research, thereby consolidating the prevalence of performativity on the life and research endeavours of many academics. The latter are nowadays often pressured to publish in ‘top’ journals to ensure they have a displayable level of performance. Drawing from literature on identity, this paper introduces and details the construction of the academic performer – a representation of identity which is increasingly typical of what it means today to be an actor in academia, in terms of attitudes and behaviour. Fundamentally speaking, this paper constitutes a critique of a detrimental tendency in academia, that is to say the excessive spread of performance measurement practices and the flow of superficiality and conformity they consolidate.
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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 | 0.025 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.010 | 0.053 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".