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LA SAPOLOGIE : DU CHOC DES CIVILISATIONS A L’IDENTITE SOCIALE DE LA POPULATION CONGOLAISE

2024· article· en· W4406395215 on OpenAlexaff
Nickson Bondo Museka, Patient MBUYU LUKAMATA

Bibliographic record

VenueStudia Universitatis Babeș-Bolyai Studia Europaea · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsNickel Institute
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Sapology: From the Clash of Civilizations to the Social Identity of the Congolese Population. Known as the art of dressing elegantly and extravagantly, sapology has become a social identity of the Congolese community. Yet, most of the population in the Democratic Republic of Congo (DR Congo) lives below the poverty line, with less than one US dollar a day. Given this controversial reality, the fundamental questions that this article attempts to answer are namely: - how have exogenous factors significantly contributed to the emergence and evolution of sapology to the point of becoming a culture and social identity of the Congolese community? - And how has sapology impacted the culture and the socio-economic situation of the Congolese community? Several studies in the literature focus on endogenous factors that construct a social identity. However, a few of them analyze how exogenous factors can contribute to constructing a culture and social identity. Using Samuel Huntington’s “clash of civilization” theory, the article demonstrates how exogenous factors have significantly contributed to the emergence of sapology to point of becoming a social identity and a modus vivendi (way of life) of the Congolese community.

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)0.002
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.014
Scholarly communication0.0060.005
Open science0.0000.003
Research integrity0.0010.002
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 head0.064
GPT teacher head0.377
Teacher spread0.313 · 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
Published2024
Admission routes1
Has abstractyes

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