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Record W4283824887 · doi:10.1177/00207152221108641

Can the social dimension of time contribute to explain the public evaluation of political change? The case of European integration

2022· article· en· W4283824887 on OpenAlexvenueno aff
Thomas Malang

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsEurobarometerPoliticsEuropean integrationEuropean Social SurveyPerceptionDimension (graph theory)Biology and political orientationSocial integrationSocial changeSociologyEconomic systemPolitical scienceSocial psychologyPolitical economyEconomic geographyPsychologyEuropean unionEconomicsLaw

Abstract

fetched live from OpenAlex

According to social theorists of time, the way societies structure and value different aspects of time plays an important role in people’s perception and evaluation of economic, political, and cultural change. I explore if two dimensions of social time—social acceleration and long-term orientation—have an effect on the public evaluation of the speed of European integration. Combining Eurobarometer data for 27 societies with measures for social acceleration and time horizons, the results show distinct patterns for the perception and preferences of European integration. Whereas I find no connection between dimensions of social time and the perceived speed of integration, more social acceleration and cultural long-term orientation lead to a desire for a slower speed of European integration. Even when controlled for other economic and political macro-factors, temporal structures can play a key role in the evaluation of political change in European societies.

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)0.005
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.265
GPT teacher head0.500
Teacher spread0.236 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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