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Record W7128129069

How Do Conceptions of Nationalism Influence Public Attitudes Towards Refugees?

2025· dissertation· en· W7128129069 on OpenAlexaboutno aff
Herbert 06/15/1995- McCullough

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismConceptualizationNational identityPoliticsPropositionPrejudice (legal term)ScholarshipPublic opinionState (computer science)
DOInot available

Abstract

fetched live from OpenAlex

This dissertation examines how the conception of national identity influences public opinion on refugees. Classic scholarship on nationalism (see Gellner, Kohn, Greenfeld) has long argued that the conception of nation (i.e., what criteria constitute membership and citizenship) shapes the political behavior of individuals within the national community. Generally, many argue that individuals living in states with less inclusive conceptions of nationalism are less trusting of outsiders. In contrast, those living in a state with a more inclusive conception of nationalism are more trusting of outsiders. However, these claims have largely been based on sweeping generalizations based on historical case studies and have not been empirically tested. On the other hand, there has been a considerable amount of work that has examined attitudes towards refugees, but these studies have focused on individual characteristics that explain attitudes about refugees, such as partisan politics, social class, exposure to refugees, prejudice and fears, and social attitudes on social inclusion and exclusion. However, what has been missing is whether how a nation is conceived affects individual attitudes. Gellner (1983), for instance, argues that as part of the nation-building process, common social attitudes and ideas of “us and them” are ingrained by the national education system to build a national identity. This dissertation examines this longstanding proposition to investigate whether such national conceptions impact attitudes towards refugees. To investigate these effects, I begin by using Cetra and Swenden’s conceptualization of different types of national conceptions: dominant, integrationist, and composite nationalism. The dissertation is built around three empirical chapters. In the first empirical chapter, I hypothesize that individuals living in a composite nationalistic state will be more accepting of refugees compared to individuals living in a dominant nationalistic state. Using a cross-national Survey from the World Value Survey (WVS) (2017-2022), I find that the influence of state conceptions on public attitudes towards refugees is limited, especially compared to individual characteristics. In the second empirical chapter, I argue that individuals exposed to dominant nationalistic views will be less accepting of refugees, while those with composite nationalistic views will be more supportive of refugees. Furthermore, those exposed to dominant conceptions of nationalism will become less accepting of refugees, while those exposed to composite conceptions of nationalism will become more accepting of refugees. Based on my survey experiment of college students in Northern Texas, I conclude that the influence of individual conceptions is a stronger predictor of attitudes toward refugees than exposure to conceptions. In the third empirical chapter, I argue that individuals living in an integrationist nationalistic substate will be less supportive of refugees compared to individuals living in the rest of the composite nationalistic state. Furthermore, individuals who have more of a composite conception of nationalism will be more supportive of refugees, while Individuals who have more of an integrationist conception of nationalism will be less supportive of refugees. Based on my case study from the Focus Canada Survey (2022), much like the second empirical chapter, I find that the influences of individual conceptions on public attitudes towards refugees are a stronger predictor than exposure to conceptions. Overall, the findings of this dissertation suggest that, at least concerning attitudes towards refugees, conceptions of nation and national community have little impact.

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)0.006
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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