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Record W2123797879 · doi:10.1177/0170840610372202

Effective Punishment Through Forgiveness: Rediscovering Kierkegaard’s Knight of Faith in the Abraham Story

2010· article· en· W2123797879 on OpenAlex
Neil Abramson, Yaroslav Senyshyn

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

VenueOrganization Studies · 2010
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsForgivenessKnightPunishment (psychology)RepentanceFaithHarmRetributive justiceCommissionSociologyLawCriminologyTheologyPhilosophySocial psychologyPsychologyPolitical scienceEconomic Justice

Abstract

fetched live from OpenAlex

Scheler (1973) proposed a model of punishment intended to re-establish a reconciled relationship between a harm doer and the person(s) harmed. Punishment was followed by genuine forgiveness, seeking genuine repentance from the harm doer, leading to the reconciliation of the relationship. This paper proposed that only a punisher having the character of a Knight of Faith (Kierkegaard 1985) could effectively implement this punishment process. The Abraham story provided an illustration of how a Knight of Faith (God) rehabilitated his relationship with Abraham using punishment and forgiveness. This process is, at an individual level, similar to one applied by Nelson Mandela in the South African Truth and Reconciliation Commission (Tutu 2000). It is argued that this process is more effective in achieving reconciliation and re-establishing effective relationships than traditional retributive approaches as typified by the Sarbanes-Oxley Act, enacted in response to the Enron and WorldCom scandals.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.333
Teacher spread0.317 · 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