Imagining institutions of man: Constructions of the human in the foundations of Ontario public schooling curriculum
Bibliographic record
Abstract
In this essay, I analyse Egerton Ryerson’s proposed curriculum for the first state-led mass public educational system in Ontario. Egerton Ryerson, Chief Superintendent of Schools in Upper Canada during the wide-scale proliferation of state schooling across Turtle Island, produced proposals for “universal” common schools, as well as proposals for residential schools for Indigenous students, segregated schooling for Black students and institutionalized schooling for disabled students and lower-class students. Following the work of Sylvia Wynter, I argue that these proposals within a supposedly universal system were not contradictory, but an organic production of Ryerson’s educational philosophy. Ryerson’s vision is organized by what Wynter terms Man, a representation for a story of the human that is overrepresented as the human itself. Through this story, claims of universal humanity are produced through the manifestation of categories of difference. In exploring how Ryerson’s universalism is structured by this understanding of what it means to be human, we see how his writings on curriculum for his common schools presage his future proposals for the violent exclusion of those who are excluded from the category of Man. Ryerson’s writings suggest that Ontario curriculum is historically founded in colonialism and imperialism (which construct the category of Man and its overrepresentation), with further implications for curricula throughout Turtle Island. This analysis points to how efforts to reform curriculum of its racist, ableist and classist roots need to rethink the very story of what it means to be human, which is wrapped up in the foundations of public 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.074 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".