Bibliographic record
Abstract
Identity and community are two theoretical terms educators use for theorizing and understanding what happens in classrooms and for designing curriculum. There are, however, serious theoretical difficulties and incongruities in which the two terms are thought, which arise from the underlying ontology of the same. In this article, I propose to think the two terms within a different ontology, one that thinks difference not in terms of its deviation from the same but that thinks difference-in-and-for-itself. This then allows us to understand identity and community as non-self-identical entities that embody change, that is, entities that have change as a constitutive feature. That is, difference-in-and-for-itself leads us to a process ontology that is consistent with past (Bakhtin, Bergson, Husserl) and present (Deleuze, Derrida, Nancy) philosophical approaches to change, evolution, and difference. To concretize my argument, I provide (a) a computer model of collective decision making as an analogy and (b) concrete examples from a second-grade mathematics lesson.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".