Review of Peter Narvaez, 'Of Corpse: Death and Humor in Folklore and Popular Culture': Logan Utah, Utah State University Press, 2003. $US24.95. ISBN 0874215595 (paper)
Bibliographic record
Abstract
Laughter is often somewhat malicious, being concerned with the fate of other people and their discomforts, incongruous experiences or at some (displayed) awkwardness. This collection of eleven papers is largely concerned with the grim humour or the macabre that is often associated with death and with the sudden (fresh) perception of the incongruous fact of one's mortality. The watching /reflective individual thereby becomes defensive, embarrassed and infinitely more self-aware.For all these papers explore aspects of the seriousness of the convergence between death and of the related mood of grim humour. While the editor's concerns began with his approach to the 'merry wake' in Newfoundland, and to losses of life at sea, he soon came to categorise such stories by the concept of 'religious fatalism', or the deeper understanding of one's frail personal mortality, in short, by a mood that is a varying mix of the serious and the ludic. Thus it - the book- joins a growing number of probing folklore studies from c. 1980 that focus on private and public traditions of death, many concerned - like contemporary legends - with the rapid social changes that have taken place in American culture in that period. The prevailing tones of these collections - and the present one - cover the full gamut from the mild and gentle to the magical, the deeply religious, the tragic and those concerned with specific spaces and with the processes and places of internment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.020 |
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".