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Record W1662897256 · doi:10.1111/jssr.12087

Compassionate Conservatives? Evangelicals, Economic Conservatism, and National Identity

2014· article· en· W1662897256 on OpenAlexaboutno aff
Lydia Bean

Bibliographic record

VenueJournal for the Scientific Study of Religion · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsProtestantismConservatismSociologyPoliticsIndividualismSolidarityPovertyPolitical scienceNational identityReligious identityPolitical economyGender studiesLawReligiosity

Abstract

fetched live from OpenAlex

In the United States, white evangelicals are more economically conservative than other Americans. It is commonly assumed that white evangelicals oppose redistributive social policies because of their individualistic theology. Yet Canadian evangelicals are just as supportive of redistributive social policy as other Canadians, even though they share the same tools of conservative Protestant theology. To solve this puzzle, I use multi‐sited ethnography to compare how two evangelical congregations in the United States and Canada talked about poverty and the role of government. In both countries, evangelicals made sense of their religious responsibilities to “the poor” by reference to national identity. Evangelicals used their theological tools differently in the United States and Canada because different visions of national solidarity served as cultural anchors for religious discourse about poverty. To understand the political and civic effects of religion, scholars need to consider the varied ways that religious groups imagine national community within religious practice.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.017
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
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 head0.060
GPT teacher head0.404
Teacher spread0.344 · 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

Citations43
Published2014
Admission routes1
Has abstractyes

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