Cultural historical research in support of inclusive classrooms:
Bibliographic record
Abstract
This article showcases the potential of dialogue within cultural historical research (CHR) to enhance our understanding of and advocacy for inclusivity in schools. It illustrates how the authors, each rooted in distinct subfields – cultural historical activity theory (CHAT) and romantic science – employ a unique approach to knowledge production regarding inclusive classrooms. By refraining from the pursuit of agreement and instead fostering an environment where their studies are juxtaposed, the authors engage in what they term “inclusive coauthoring,” approaching each other’s methodologies with an asset-based, solidarity-seeking stance. The first author utilizes excerpts from an ethnographic study in an elementary classroom to demonstrate how CHAT can elucidate the intricate dynamics of diverse classrooms, shedding light on mechanisms of inclusion/exclusion and identifying potential barriers (opportunities) to inclusive practices. On the other hand, the second author illustrates how a romantic science perspective can empower educators to cultivate inclusivity in ways previously unexplored before their deep engagement with the study. Uniting in collaboration around shared goals rather than shared methods, led the authors to unforeseen advancements, particularly in one of the studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.016 | 0.057 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".