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Record W4381461247 · doi:10.5539/jsd.v16n4p22

Multiparty Democracy, Social Cohesion, and Human Development in Sub-Saharan Africa: A Conceptual Framework

2023· article· en· W4381461247 on OpenAlexvenueno aff
Hamidou Issaka Diori, Anchana NaRanong

Bibliographic record

VenueJournal of Sustainable Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)DemocracyHuman development (humanity)Conceptual frameworkDevelopment economicsSociologyPolitical scienceEconomic systemPolitical economyEconomic growthSocial scienceEconomicsPoliticsLaw

Abstract

fetched live from OpenAlex

This paper proposes some assumptions regarding the complex relationship between multiparty democracy, social cohesion, and human development in Sub-Saharan Africa. A conceptual framework was used to map out this relationship. We assumed that because multiparty democracy is relatively new in Africa and increasingly challenging for most countries, its relationship with human development may neither be proximal, nor positive. With respect to social cohesion, we assumed that a socially cohesive society is more likely than a non-cohesive one to promote human development. Further, we assumed that although multiparty democracy is susceptible to exerting a negative or weak effect on human development, the relationship may be mitigated by the level of social cohesion. The immediate implication of this assumption is that multiparty democracy is likely to improve the well-being of the populations of sub-Saharan Africa if the degree of social cohesion is relatively high. The proffered assumptions may be of great interest for practitioners and researchers in human development studies and other relevant fields.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.295
Teacher spread0.263 · 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 teacher head, not a consensus.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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