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Record W2968655777 · doi:10.32872/spb.v14i2.33399

The Role of Control Motivation in Germans’ and Poles’ Interest in History

2019· article· en· W2968655777 on OpenAlexaff
Michał Bilewicz, Anna Stefaniak, Markus Barth, Marta Witkowska, Immo Fritsche

Bibliographic record

VenueSocial Psychological Bulletin · 2019
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsCarleton University
FundersNarodowe Centrum NaukiDeutsche Forschungsgemeinschaft
KeywordsMoralityPopularityCompetence (human resources)CuriositySocial cognitive theory of moralityAgency (philosophy)Social psychologyMoral agencyPerceptionPsychologyCognitionControl (management)Moral developmentSociologySocial sciencePolitical scienceLawManagement

Abstract

fetched live from OpenAlex

Contemporary societies seem to be obsessed with history. This is reflected in the popularity of historical books, films, and reenactments. In our research, we aimed to assess the specific types of content that interest people when exploring their national histories and the psychological factors motivating such explorations. Following the two-dimensional model of social cognition that points to morality and competence as the main dimensions in individual and group perception, we distinguished interest in competence-related aspects of national history (control) from interest in historical moral actions (moral agency). Two studies performed in Poland and Germany showed that in both countries people’s interest in history is structured in a similar way, in which moral agency and control play essential roles. Additionally, in both countries people reacted to individual control threats with enhanced curiosity about the past moral agency of their nations. We discuss these results within the framework of the model of group-based control and compensatory control processes.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.999

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)0.0020.000

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 head0.087
GPT teacher head0.340
Teacher spread0.254 · 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 designObservational
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

Citations3
Published2019
Admission routes1
Has abstractyes

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