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Record W1608271276 · doi:10.1002/nvsm.1418

The international expansion of religious organizations in Africa

2012· article· en· W1608271276 on OpenAlexaff
André Richelieu, Bernard Koraï

Bibliographic record

VenueInternational Journal of Nonprofit and Voluntary Sector Marketing · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInternationalizationGlobalizationPhenomenonLeverage (statistics)SociologyMarketingOrder (exchange)Religious organizationContext (archaeology)Political sciencePublic relationsBusinessEpistemologyGeographyLawInternational trade

Abstract

fetched live from OpenAlex

The marketing of religion remains a large research area to explore, simply because the studies that have been conducted are mostly applications of a marketing mix to the religious offer. In the context of globalization, it is surprising that the internationalization of religious organizations remains an uncovered subject because Christian religions have a biblical mission to become international. This paper explores the phenomenon of the internationalization of religious organizations in order to better understand their preferred expansion modes in Ivory Coast, since Western evangelist Christian communities in West Africa have flourished in recent decades. The current analysis allows us to draw a conclusion that the process of religious expansion is truly the result of a strategic reflection supported by marketing tools and communication. This emphasizes the role of marketing as a leverage for profit and nonprofit organizations, as well as its growing importance as a means for appealing to the masses among new Christian communities of Third World countries. Copyright © 2012 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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

Citations24
Published2012
Admission routes1
Has abstractyes

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Same venueInternational Journal of Nonprofit and Voluntary Sector MarketingSame topicReligion, Society, and DevelopmentFrench-language works237,207