Bibliographic record
Abstract
We argue that locating “woke” as a left-wing project does a disservice to the traditional left-wing views that are grounded in the Enlightenment demand of respect for persons, and the firm belief that reasoned dialogue is the most effective pathway to human progress. We note, using an example from Canadian politics, that “woke” tactics are problematic precisely because they are divisive in the sense of making reasoned dialogue unlikely. We argue that, though wokesters pride themselves on being “progressive,” such a title is not deserved since their focus makes them comfortable companions with those often considered reactionary. We then reflect on Kant’s argument that the most important Enlightenment message is that we ought to trust reasoned dialogue rather than authority in deciding what to believe or do, and then argue that that this translates into three “attitude directives” with regard to discourse: (i) let them speak, (ii) avoid insult, and (iii) keep the discourse focused on the most urgent problem, namely, economic inequality. Finally, we examine the educational implications that emerge from our journey and suggest that the core command is that challenge, rather than safety, ought to be the motto of all educators.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.053 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".