The importance of critical judgment in uncertain disciplines: A comparative case study of undergraduate fine art visual practice
Bibliographic record
Abstract
Criticality is an important means to negotiate uncertainty, which has become a characteristic of teaching and learning conditions in postmodern times. This paper draws from an empirical comparative case study conducted in the uncertain discipline of fine art visual practice, where critical judgement and meta-cognition are important for professional contemporary art practice. Charting the curricula intended by staff and the culture experienced by students, the paper considers the relation between the espoused theory of criticality in two art schools and their theory-in-use within assessment structures and cultures. Emphasis is placed on the significance of such approaches to criticality for the student experience and their learning engagement. Emerging discourses of ‘subjectivity’ and a lack of development of student meta-cognition indicated that, at an undergraduate level of study, the curricula of these cases are unwittingly underpreparing their graduates for operating with agential criticality as they enter the uncertain context of contemporary art.
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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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".