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Record W2029508289 · doi:10.1080/15283488.2013.776497

Remembering Your (Im)Moral Past: Autobiographical Reasoning and Moral Identity Development

2013· article· en· W2029508289 on OpenAlexafffund
Tobias Krettenauer, Maureen Mosleh

Bibliographic record

VenueIdentity · 2013
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyMoral developmentMoral disengagementSocial cognitive theory of moralityIdentity (music)Social psychologyMoral reasoningNarrativeMoral psychologyMoralityDevelopmental psychologyEpistemology

Abstract

fetched live from OpenAlex

Narratives about positive and negative life events have been shown to be associated with identity development. The present study extends this line of research by investigating how individuals’ autobiographical memories about their past immoral and moral actions relate to moral identity development. The authors interviewed 131 participants from 3 age periods (adolescence, emerging adulthood, adulthood) about past events in which they did something right or wrong and felt either good or bad about it. The authors assessed moral identity development by the self-centrality of moral values and by internal moral motivation. Results demonstrated that older participants and participants with higher internal moral motivation drew stronger connections between their current self and past moral and immoral actions. Moreover, individuals with higher internal moral motivation more often acknowledged the conflicting nature of these events. Taken together, the findings indicate that the way individuals remember their own (im)moral past is associated with moral identity development.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.320
Teacher spread0.279 · 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 designQualitative
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

Citations16
Published2013
Admission routes2
Has abstractyes

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