Deconstructive Misalignment: Archives, Events, and Humanities Approaches in Academic Development
Bibliographic record
Abstract
Using poetry, role play, readers’ theatre, and creative manipulations of space through yarn and paper weaving, a workshop in 2008 challenged one of educational development’s more pervasive and least questioned notions (“constructive alignment” associated most often with the work of John Biggs). This paper describes the reasoning behind using humanities approaches specifically in this case and more generally in the Challenging Academic Development Collective’s work, as well as problematising the notions of “experiment” and “results” by unarchiving and re-archiving such a nonce-event. The critical stakes in using an anti-empirical method are broached, and readers are encouraged to experience their own version of the emergent truths of such approaches by drawing their own conclusions. En 2008, par le biais de la poésie, du jeu de rôles, du théâtre lu et de manipulations créatrices de l’espace avec de la laine et des tissages en papier, un atelier a mis au défi une des notions les plus généralisées et les moins remises en question du développement éducatif, l’alignement constructif, le plus souvent associé aux travaux de John Biggs. Cet article décrit le raisonnement qui se cache sous l’utilisation des approches des humanités tout spécialement dans ce cas et de manière plus générale dans les travaux du Collectif sur le développement académique stimulant. L’article traite également de la problématique sur les notions d’« expérience » et de « résultats » en désarchivant et en réarchivant une telle circonstance. Les enjeux principaux de l’utilisation de cette méthode anti-empirique sont abordés et les lecteurs sont encouragés à faire l’expérience de leur propre version des vérités qui émergent de telles approches en tirant leurs propres conclusions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".