Pedagogy of the Deceased: The Cemetery as a Classroom for Community Development and Hope
Bibliographic record
Abstract
As individuals and as communities, how do we learn to recognize that death contributes to life? The purpose of my research is to explore how matters pertaining to death and mortality can teach us to connect everyday personal experiences with issues of injustice, violence, and ecological crisis. Working with Freirean critical pedagogy in conjunction with key insights from the North American death education movement, my research lays groundwork for an innovative “pedagogy of the deceased” whereby humanizing praxis (as per critical pedagogy) can be integrated with death-inclusionary praxis (as per death education). By way of contextualizing and embodying this integrated pedagogy of the deceased, my research includes a place-based component (based in Waterloo, Ontario) involving a group of eleven people who participate in a series of Cemetery Café meetings in two local cemeteries. While recognizing the very wide array of funerary traditions (cremation, burial, sky burial, etc.) including many traditions in which the significance of mortality does not depend on any particular site, my research focuses on the cemetery as one particular place in which community-based education can be usefully facilitated. The Cemetery Café includes discussions, embodied learning activities, individual reflection, and group brainstorming about how the cemetery can foster community development and hope. Datasets include one-to-one interviews, group-generated flipchart papers, photographs, individual homework assignments, and my own researcher field notes. Following an integrative-interpretive approach, I first analyze the “who” of the pedagogy of the deceased by asking who gets to participate in this pedagogy. Secondly, I analyze the cemetery as a classroom, including consideration of how the cemetery can be a place for embodied learning. Thirdly, I analyze what kind of consciousness is cultivated within this pedagogy, and I explore the relationship between human mortality and critical consciousness. In line with the aforementioned analytical work, I conclude by looking at (1) indigenizing the cemetery and our view of mortality, (2) establishing teaching cemeteries (along the lines of teaching hospitals), (3) advancing an ecological approach to death and cemeteries through such practices as green burial, and (4) working and hoping for an end to violence.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| 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".