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Record W3199269136

Rethinking Religion and Ethnicity in Comparative Politics: Lessons from Africa

2015· article· en· W3199269136 on OpenAlexaff
Owuraku Kusi-Ampofo

Bibliographic record

VenueSSRN Electronic Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEthnic groupPoliticsComparative politicsSociologyPolitical scienceModernization theoryPolitical philosophyGender studiesSocial sciencePolitical economyPositive economicsLawAnthropologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the extent to which existing approaches/theories in comparative politics have defined, referenced and integrated religion and ethnicity in their analysis. Religious and ethnic cleavages invite comparative politics scholars to interrogate an individual's attitudes, values, and beliefs in other to explain the differences and similarities we find among nations and peoples (Caramani 2011, 2009). Indeed, ethnic and religious cleavages play significant roles in shaping a person's world view and their political attitude. To answer important questions about the roles that ethnicity and religion play in comparative politics, this paper compares different approaches and theories of comparative politics, including modernization theory, rational choice, political culture, dependency theory, institutionalism, and poststructuralist theories. Thus, a consciousness of the influence that ethnic and religious identities have over an individual and a community also helps to solidify the relationship between theory and methods in comparative politics.

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)0.018
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0070.021
Scholarly communication0.0070.017
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.075
GPT teacher head0.352
Teacher spread0.277 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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