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Record W4381487543 · doi:10.1086/724241

Speaking of Failure: Modern Masculinity and Medieval Confession

2023· article· en· W4381487543 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSigns · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsCalgary Laboratory Services
Fundersnot available
KeywordsPenitentialConfession (law)MasculinityPatriarchyPower (physics)Gender studiesSociologyHegemonyHegemonic masculinityHistoryLawPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Modern hegemonic masculinity often entails a focus on the past, a longing for an imagined time when men had more authority and power. I argue that this orientation toward the past stretches back to the Middle Ages. Specifically, the discourses surrounding medieval confession—the mandatory ritual of confessing one’s sins to a priest—continue to shape how white men assert their own power and domination in modern North America. In Europe’s Middle Ages, guides to confession encouraged men to assert their patriarchal authority by narrating their own past failures. Through an analysis of representative medieval penitential manuals, I show how confession became a discursive tool for men to imagine themselves in positions of social and moral superiority. This penitential tradition’s continuing influence is particularly evident in North America’s booming men’s self-improvement culture and the growing nostalgia for historical versions of masculinity. By narrating the sins of their own past and their collective flawed past as men, North American men enact a modern penitential masculinity that does not undermine patriarchy but rather justifies their place as powerful men within it. Western patriarchy has long relied on a penitential model of masculinity that deploys men’s past failures—both individual and collective—as a justification for future gendered domination.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.332
Teacher spread0.273 · 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