A humanities-based pedagogy of death : apocalyptic prose as public reimbursement collapse competency
Bibliographic record
Abstract
The purpose of this humanities-based inquiry is to explore how poetic prose within apocalyptic fiction opens to realities of mourning and relationality, each a component in the ways in which imagined systems in collapse are nurtured in the process of dying. I conceive of mourning to mean a recognition of real loss and a response that is softened to the realities of grief without being paralyzed by its depth. I conceive of relationality as the experienced impacts of relation with more-than-human kin and ancestors and the as-yet-born, as these relations provide comprehensive understandings of entangled ways of being, including death. The systems in collapse are located in public reimbursement, the systems that provide or prohibit drug and device accessibility within Canada. From the lens of the reimbursement realities of Type 1 diabetes, I identify these systems as being removed from the needs of patients, a series of actions that consistently fail to be responsive to the realities of persons with disease. These systems underscore the ways the exclusion of the oppressed (patients) from the decision-making of the oppressors (the producers and the distributors of health technologies) necessitates the current or future death of the system. Using select works of Paulo Freire and Boaventura de Sousa Santos, this systems death is explored through the lens of abyssal thinking. Since I have now identified the perceived collapse, in this work I attempt to destabilize conventional models of repair-through-progress by advantaging the process of hospice. Here, hospicing does not refer to conventional hospice programs, but instead draws from an unconventional source to explore ways in which a pedagogy of death can be applied across or within broad systems death: the poetry of apocalyptic fiction within Cormac McCarthy’s The Road. Two thematic elements, mourning and relationality, are applied as a poetic lens through which to invigorate imaginaries on the constituent parts of death, the macabre-ness of the reanimated corpse or the repulsion of fetid flesh. These elements urge a leaning-in to death, to become familiar with death, in order to speak to collapse and support the eventual demise of the modern system.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.080 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.012 |
| 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".