Learning to Be: Emerging Discourse in Awakening Transformation in Education
Bibliographic record
Abstract
This paper explores the disconnection between knowledge of social and environmental injustices and actions to right them. Through our discussion, we consider possible reasons for this disconnection, whether a lack of knowledge, personal accountability and responsibility, or a fear of being swallowed up in the depths of the suffering in the world. We then critically reflect on our role and the role of education to broach this gap. We adopt O’Sullivan’s (2002) transformative learning theory as a guide and suggest that disruptive dialogues, like the one that has guided this paper, can challenge habits of mind, shift perspectives, and lead to action for a better, more equitable world. Ultimately, we conclude that such conversations are organic and ever changing and are integral to education.Keywords: Social justice; critical discourse; transformation
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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 | 0.027 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.022 | 0.125 |
| Scholarly communication | 0.023 | 0.033 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.008 | 0.014 |
| 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".