Bibliographic record
Abstract
In the spring of 2008, the Literacy and Numeracy Secretariat of the Ontario Ministry of Education in Canada released a DVD that was one in a series designed to train literacy teachers in what the Ministry referred to as ‘high-yield’ comprehension strategies. Using the lens of Critical Race Theory, this article analyses the picture book used in the model lesson as well as the teaching methods recommended for all Ontarian teachers in the DVD. While the selection of the picture book fits the present policies of multiculturalism in Ontario, its romanticized portrayal of an indigenous people serves to perpetuate racism, particularly in the uncritical reading demonstrated in the DVD. In addition, the teaching methods demonstrated as ‘high-yield’ arise from the global movement towards standardization in education, and establish measurable student achievement, in a classroom portrayed as socially neutral, as the end goal of education. Nowhere in this model lesson, given in a multiracial classroom where minority races are both invisible and deficit, is difference acknowledged as present or important. The result is that this DVD, designed to be used as a training resource in all Ontarian elementary schools, serves to re-inscribe the whiteness of literacy practice in Ontario, and to silence the possibilities for debate and negotiation that are the hallmarks of democratic education.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".