Bibliographic record
Abstract
This article proposes anti-currere as a non-philosophical intervention in curriculum theory, drawing on the work of François Laruelle to challenge the field’s foundational obsession with the Real. It argues that curriculum study, despite its surface diversity, remains structurally wedded to a philosophical decision that monopolizes reality by predetermining what is thinkable. Through incisive critique of canonical concepts like the planned/lived curriculum binary, the paper reveals how curricular discourse habitually reproduces the very structures it claims to disrupt. In response, anti-currere is posited as a radical strategy of withdrawal from the decisional compulsions of the field – a minoritarian, non-standard mode of thought that reorients curriculum toward the immanence of the Real rather than its capture. Rather than offering another curriculum-as-x, anti-currere opens a space for stranger, generic curricular thought unbound by the auto-production of identity, representation, and method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".