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Record W7130358675 · doi:10.3167/ds2025.290105

Of Halos and Horrors

2025· article· W7130358675 on OpenAlexaboutno aff
Hermanpreet Singh, Ronjon Paul Datta

Bibliographic record

VenueDurkheimian Studies · 2025
Typearticle
Language
FieldSocial Sciences
TopicEmile Durkheim and Sociology
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsMythologyAutonomyFeelingValue (mathematics)DevaluationTrope (literature)

Abstract

fetched live from OpenAlex

Abstract Drawing on a radical Durkheimian framework, this article analyses neoliberal morals, myths and the politics of ageing, particularly during the Covid-19 pandemic in Ontario, Canada, in which an inordinate number of elderly persons in long-term care died. Examining prevalent collective representations, we contend that older persons are differentially valued through two opposing yet structurally related sacral logics: the heroic and the abject . These logics express how neoliberal societies assign value to older populations through myths about moral purity and impurity, abjection, and sacredness. The heroic older person embodies neoliberal ideals of autonomy and self-management, while the abject form, defined by dependency, becomes disposable. During the pandemic, these subjective forms were mediated by a moral dynamic that we call fatalistic altruism , in which older persons accept their devaluation while feeling obligated to self-sacrifice. These dynamics reveal a deeper, pathological politics surrounding ‘the cult of humanity’.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.041
Scholarly communication0.0080.004
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.048
GPT teacher head0.394
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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