Social Imaginaries and Epistemic Systems in Ontario's Institution of Public Education
Bibliographic record
Abstract
This dissertation seeks to analyze Ontario’s public education system for the explicit and implicit epistemic commitments that instantiate the institution’s goals, methods of evaluation, and practices. The analysis proceeds with the conceptual framework of social imaginaries, highlighting underlying epistemic systems and their socially constructed central significations which organize and govern the norms of a society and manifest in institutions and epistemic resources. The dominant, operative, instituted social imaginary in Ontario is instantiated by the epistemology of mastery. The central significations of the epistemology of mastery are its ensemblistic-identitary logic, and its overarching goal of control or mastery. In my analysis, this epistemic system is contrasted with a newer system, ecological epistemology, which exists as the result of the social imaginary’s instituting power, the society’s critical-creative ability to create new meanings and significations. The central significations of ecological epistemology are situated epistemic location, co-constitutive relationality, and local responsivity. I analyze Ontario’s institution of public education by identifying and comparing the significations of an epistemology of mastery with the significations of ecological epistemology found within its material resources, primarily within policy documents. It is my contention that a continued dependence on the epistemology of mastery impedes significant institutional change, despite evidence of the desire to institute the significations of ecological epistemology. The epistemology of mastery can contribute to undue harm to children in the schooling system, specifically in the form of epistemic injustices, which have both epistemic and ethical dimensions. The hegemonic status of the epistemology of mastery as instituted in Ontario’s public education system harms children as epistemic agents, which causes secondary harms to other members of epistemic communities and to the very processes of knowledge circulation. One framework for thinking about epistemic injustice, described by Kristie Dotson as epistemic exclusions, explains that these harms occur at different magnitudes, with each requiring different tactics to counter. Through an ecological analysis, I aim to show why public education in Ontario needs to embrace the significations of ecological epistemology to unsettle the hegemonic status of the epistemology of mastery: to lessen instances of epistemic injustice and to make space for alternative epistemic systems, new and resurgent, that can help us create solidarities and coalitions and (re)imagine our futures.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.036 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".