Bibliographic record
Abstract
Spring is a season of renewal and transformation and each of the articles in this March, 2023 issue reflect that spirit.As curriculum scholar Dwayne Donald reminds us: "A significant curricular and pedagogical challenge faced by educators in Canada today is how to facilitate a new story that can repair inherited colonial divides and give good guidance …" (Donald, 2021).The articles in this issue contribute to our collective understanding of transformative possibility addressed at historic patterns of educational inequality.The first three articles engage a story that looks at the genesis of inequitable educational outcomes as being sourced from educational structures and practices, rather than the entrenched deficit orientation that sources students and their communities as the problem.For some this is a new story, for some an old story that needs recognition, but the key point is how do we facilitate this new(er) story?These educational researchers do this work through naming the colonial and white supremacist nature of schooling in Canada, and shift the focus of analysis and intervention from fixing students to fixing educational structures that unfairly impact Indigenous and Black students.They provide sorely needed analysis and guidance to address long-standing inequalities, highlighting the significance of engaging with community voice and involvement in supporting transformative possibilities in educational settings.The fourth article in this collection helps us consider the affective nature of this work as we tell new(er) stories, and the demand to look backwards and forward in time as we consider our present through more than the intellect.
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 | 0.037 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.059 | 0.049 |
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".