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Record W1508573204 · doi:10.5539/jpl.v8n2p7

Third Parties and Electoral Politics in Ghana’s Fourth Republic

2015· article· en· W1508573204 on OpenAlexvenueno aff
Eric Yobo, Ransford Edward Van Gyampo

Bibliographic record

VenueJournal of Politics and Law · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican studies and sociopolitical issues
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsDemocracyElectoral politicsIdeologyElectoral geographyPolitical sciencePolitical economyGovernment (linguistics)General electionThe RepublicPresidential systemPresidential electionOrder (exchange)Public administrationSociologyLawEconomics

Abstract

fetched live from OpenAlex

Since the inception of Ghana’s fourth attempt at constitutional democracy in 1992, third parties have performed abysmally in the nation’s electoral politics. The quest and hope for a third force in Ghanaian electoral politics has always been dashed after every election. This article places the electoral performance of third parties in Ghana’s Fourth Republic under microscopic view and interrogates the nature of their pitiable electoral performance, and its implications on Ghana’s multiparty electoral democracy. The paper analytically demonstrates the progressive decline of third parties’ electoral output despite their active participation in both presidential and parliamentary elections. It argues that, although third parties’ electoral fortunes appear utterly gloomy, showing no realistic chance of forming government, they augment Ghana’s multiparty democratic politics. In order to make any meaningful incursion and impact in Ghanaian electoral politics, the paper will recommend the need for third parties with shared political ideology to reorganize under a uniform umbrella to become more electorally competitive in the future.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.053
GPT teacher head0.338
Teacher spread0.285 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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