Woke Culture in Canada? Anthropological Errors and Opportunities for Mission
Bibliographic record
Abstract
With the recent emergence of the so-called “woke culture” in North America and Europe, and given the wide variety of ways “woke” has been interpreted by Christians, this paper begins by defining “woke culture” through the lens of anthropology: what is “woke culture” and what does it presuppose about the meaning of being human? The paper argues that “woke culture” carries within it the seeds of an anthropological error: it ignores the original evidence of the giveness of an embodied identity, including both the inherent meaningfulness of having received one’s body from another, and the significance of its sexual differentiation as male or female. A reduced understanding of human freedom as pure “self-making” also follows. By contrast, Pope John Paul II presents an adequate anthropology by placing embodied human experience at its center. Taking Canada as a case study for “woke culture,” examples from the three fundamental anthropological categories of birth, love (sexual difference) and death are discussed. In the face of the great confusion generated by this new category of “woke,” assessing its anthropological foundations prepares those who are engaged in Catholic education or pastoral work to respond adequately to the challenges it brings. The paper invites both a critical reading of woke culture, and a fearless creativity to be present within it.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.049 | 0.031 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| 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".