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Record W4288043368 · doi:10.5539/ijef.v14n8p36

A Literature Review of Privatization Models, Theoretical Framework for Nigerian Railway Corporation Privatization

2022· review· en· W4288043368 on OpenAlexaffvenue
Oye Abioye

Bibliographic record

VenueInternational Journal of Economics and Finance · 2022
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsUniversity College of the North
Fundersnot available
KeywordsProfitability indexCorporationProductivityBusinessPrivate sectorInvestment (military)Government (linguistics)FinanceIndustrial organizationState (computer science)EconomicsMarket economyEconomic growth

Abstract

fetched live from OpenAlex

Privatization is the transfer of ownership from the state to the private sector. The main idea behind this economic strategy is to relieve government from the saddle of management of state enterprises that can be seen to be best managed by the private sector for maximum performance. The main method and critical choices for the privatization of the Nigerian Railway Corporation are management-buyout, concession, management contract, leases, share option and franchises. In addition, the research paper discusses the main performance indicators, such as effectiveness, efficiency, productivity, infrastructural investment, and profitability. These are the parameters set to measure the performance of privatized state enterprises after privatization discussed in the research study.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.834
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.033
GPT teacher head0.260
Teacher spread0.227 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations2
Published2022
Admission routes2
Has abstractyes

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