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Social Psychology, Moral Character, and Moral Fallibility*

2008· article· en· W2137003987 on OpenAlexaff
Lorraine Besser-Jones

Bibliographic record

VenuePhilosophy and Phenomenological Research · 2008
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCharacter (mathematics)MistakeMoral characterEpistemologyPsychologyGood moral characterSociologyPhilosophyMoral disengagementLawPolitical science

Abstract

fetched live from OpenAlex

In recent years, there has been considerable debate in the literature concerning the existence of moral character. One lesson we should take away from these debates is that the concept of character, and the role it plays in guiding our actions, is far more complex than most of us initially took it to be. Just as Gilbert Harman, for example, makes a serious mistake in insisting, plain and simply, that there is no such thing as character, defenders of character also make a mistake to the extent that they imply there is no problem raised by the psychological literature for either the concept of character or the nature of character‐based ethics. My hope for this paper is to avoid both of these mistakes by first, exploring exactly what is the concept of character that is so firmly rooted in our philosophical and everyday thinking; and second, exploring the implications of the psychological literature for this appropriately understood concept of character. In so doing, I will come to a resolution that vindicates the existence of character, while at the same time calls attention to the real and serious problem suggested by the psychological evidence. This, we will see, is a problem of moral motivation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.706
GPT teacher head0.448
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations47
Published2008
Admission routes1
Has abstractyes

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