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Record W2903812455 · doi:10.1080/23269995.2018.1513250

Neo-Gnosticism, ideology and the culture wars: the contemplative antidote – perennial tensions: a reply to Jersak

2018· article· en· W2903812455 on OpenAlexaff
Ron Dart

Bibliographic record

VenueGlobal Discourse · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy, Ethics, and Existentialism
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsGnosticismContemplationIdeologyPoliticsPhilosophyPeacemakingSociologyReligious studiesLawAestheticsEnvironmental ethicsEpistemologyTheologyPolitical science

Abstract

fetched live from OpenAlex

This reply speaks to Brad Jersak's analysis of the left–right culture wars spectrum and his critique of identity politics. He offers an alternative rooted in his studies of George P. Grant and Simone Weil's notion of the primacy of the Good vis-à-vis the triumph of the will that undergirds modernist assumptions. Jersak's thesis is confirmed and would be strengthened by careful attention Eric Voegelin's assessment of Gnosticism in The New Science of Politics. What needs further attention on the way of just peacemaking is the important turn from the vita activa to a sustained vita contemplativa as a way of knowing and being (cf. Merton). Finally, using Hermann Hesse's The Glass Bead Game (1946) reminds us of the inevitable clash between idealists and realists, raising the question of how, in the end, the owl of contemplative wisdom might navigate conflict between doves and hawks.

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)0.012
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.024
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0110.046
Scholarly communication0.0120.021
Open science0.0030.008
Research integrity0.0240.028
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.048
GPT teacher head0.317
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2018
Admission routes1
Has abstractyes

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