Bibliographic record
Abstract
This work is a philosophical examination of the relevance and function of socio-political myths in education. Central to this work is exploring the antinomy between myth and reason. Drawing on the work of philosopher Hans Blumenberg, I defend his view that one should go beyond the myth and reason antinomy and understand myth as an important and unique mode of symbolic orientation that, along with reason and science, is an essential part of humanity’s symbolic interaction with the world. From this view, I explore how socio-political myths are philosophically and practically relevant to the analysis of society in general and education specifically. Of particular importance, I argue that a philosophical understanding of ‘socio-political myth’ should be integrated as part of the critical democratic conception of education. By integrating a substantive philosophical understanding of socio-political myths into the critical democratic framework, a number of important pedagogical implications are revealed. Specifically, this work reveals how two particularly powerful socio-political myths that are currently embedded in the Canadian education system, the meritocratic and neoliberal myths, ultimately erode and undermine values, beliefs and educational practices that are consistent with democracy. In addition, I contend that socio-political myth should be understood as an important and necessary narrative corollary to critical democratic praxis. As such, I conceptualize and defend what I denote as democratic myth as an essential narrative to the development of critical participatory democracy both in and through education. Finally, I conclude this work by examining how democratic myth may be practically developed by teachers and students.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.060 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".