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Record W4295068505 · doi:10.1177/00207152221115631

Contrasting perspectives: Belief in national superiority in relation to countries’ performance

2022· article· en· W4295068505 on OpenAlexvenueno aff
Marharyta Fabrykant, Vladimir Magun

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNormativeWorld Values SurveySocial psychologyPopulationPsychologyDeveloping countryPolitical scienceSociologyEconomicsEconomic growthDemographyLaw

Abstract

fetched live from OpenAlex

This article examines cross-country differences in the strength of individuals’ belief that their country is better than most others and the dependence of this belief on their country’s performance in various spheres. The research design consists of a series of multilevel ordinal logistic regression models estimated using the data of the most recent thematic wave of the International Social Survey Programme (ISSP)—National Identity module. Our research finds that these effects are mostly nonlinear U-shaped: people from both high- and low-performing countries express a strong belief in their country’s superiority, while people from average-performing countries do not. These findings suggest a bifurcated nature of belief in national superiority—an interplay between a grounded estimation of a country’s actual achievements and the social norms and individual motivations that prescribe holding one’s own country in high esteem regardless of its actual performance. These norms are found to be the strongest in underperforming countries, while in average- and high-performing countries, people making these evaluations are under weaker normative pressure and therefore more attuned to country achievements. As a result, the weakest belief in national superiority is found not in underperforming, but in average-performing countries. The latter also have the highest diversity on this belief, probably because different segments of the population compare their country’s performance against different benchmarks.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.417

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.378
Teacher spread0.322 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2022
Admission routes1
Has abstractyes

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