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Record W4391109799 · doi:10.1177/07352751231223203

Morality, Affect, and Reputation in the Making of a Motivated Social Self

2024· article· en· W4391109799 on OpenAlexaff
Seth Abrutyn, Jienian Zhang

Bibliographic record

VenueSociological Theory · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSymbolic interactionismReputationSociologySocial psychologyMoralityConstruct (python library)EpistemologyAffect (linguistics)SelfContext (archaeology)PsychologySocial scienceComputer science

Abstract

fetched live from OpenAlex

Despite the prevalence of symbolic interaction’s theory of the self, alongside alternative implicit models in dual-process and practice theory, sociology continues to struggle with incorporating affect into models of the self. To address this gap, we distinguish between the conventional sociological understanding of Goffman’s self as cynical and masked and an alternative construct we excavate by paying close attention to negative cases like Goffman’s Asylums and Stigma. This alternative theory of self treats self and situation not as one-sided but as mutually constitutive. Unlike most models of self, our alternative is continuously motivated by humans’ desire to maintain reputation within a given situation; reputation making is dependent on the situation, and its ceremonial rules provide the context for the self’s realization of affective rewards. After considering how reputational claims around ceremonial rules reveal an affectively driven, moral self, we consider the theoretical and methodological implications of the theory for major strands within symbolic interactionism.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.031
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.391
Teacher spread0.331 · 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 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

Citations11
Published2024
Admission routes1
Has abstractyes

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