MétaCan
Menu
Back to cohort
Record W2121875107 · doi:10.1177/2158244014529777

Honor on Death Row

2014· article· en· W2121875107 on OpenAlexafffund
Judy Eaton

Bibliographic record

VenueSAGE Open · 2014
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsWilfrid Laurier University
FundersWilfrid Laurier University
KeywordsHonorRemorseArgument (complex analysis)PolitenessNarrativeCriminologyPsychologySociologySocial psychologyPolitical scienceLawLinguistics

Abstract

fetched live from OpenAlex

The Southern United States is described as having a culture of honor, an argument that has been used to explain higher crime rates in the Southern United States than in the rest of the country. This research explored whether the combination of honor-related violence and traditional southern politeness norms is related to regional differences in the degree of remorse expressed by those who have committed violent crimes. It was proposed that different social norms regarding politeness and apologies in the Southern United States would be reflected in the narratives provided by offenders. The data came from the final statements that offenders on death row made before they were executed. Results showed that, compared with offenders executed in the non-Southern United States, offenders executed in the South more often apologized for their crimes in their final statements, but they were not necessarily more remorseful.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.716
Threshold uncertainty score0.997

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)0.0050.004

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 head0.037
GPT teacher head0.357
Teacher spread0.320 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations8
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueSAGE OpenSame topicForgiveness and Related BehaviorsFrench-language works237,207