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Record W3110403207 · doi:10.5296/jpag.v10i4.17732

The Complexity of Business-Government Relations in Ghana: Implication for State-Market-Society Nexus

2020· article· en· W3110403207 on OpenAlexaff
Eugene Danso

Bibliographic record

VenueJournal of Public Administration and Governance · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsBrock University
Fundersnot available
KeywordsNexus (standard)DivestmentIdeologyGovernment (linguistics)GlobalizationState (computer science)Product (mathematics)Market economyBusinessEconomic systemEconomicsEconomyPolitical economyPoliticsPolitical scienceFinance

Abstract

fetched live from OpenAlex

The complexity of business-government relations in the globalized economy cannot be underestimated. This is the product of the cross-cutting effects of a long-term policy shift heightened by globalization, coupled with privatization. Central to this, is the emergence of ideologies within the contours of the state-market-society landscape. Ghana’s privatization experience is typical of this major ideological approach to business-government relations. As a qualitative study, this paper adopts unobtrusive content analysis of an empirical study of the privatization of Ashanti Goldfields Company (AGC). This paper argues that Ghana’s adoption of privatization policy has yielded undesirable policy outcomes due to the complexities of the divestiture process which had adverse effect on the state-market-society nexus.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.014
Scholarly communication0.0040.006
Open science0.0000.002
Research integrity0.0010.001
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 head0.051
GPT teacher head0.251
Teacher spread0.200 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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