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Record W3139258220 · doi:10.7916/d8-dbs8-p927

Nigeria’s Petroleum Industry Bill: A Missed Opportunity to Prepare for the Zero-Carbon Future

2021· article· en· W3139258220 on OpenAlexaboutno aff
Solina Kennedy, Perrine Toledano, Martin Dietrich Brauch, Tehtena Mebratu-Tsegaye

Bibliographic record

VenueSSRN Electronic Journal · 2021
Typearticle
Languageen
FieldEnergy
TopicOil, Gas, and Environmental Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum industryQuarter (Canadian coin)PetroleumEnergy sectorBusinessWindow of opportunityEconomic growthEconomyEconomic policyEngineeringEconomicsNatural resource economicsGeography

Abstract

fetched live from OpenAlex

With Nigeria’s National Assembly debating the proposed Petroleum Industry Bill (PIB) in the first quarter of 2021—after nearly two decades of attempted reform of the country’s petroleum sector—Nigeria has a unique opportunity to rethink the role of the oil and gas industry in Nigeria’s economy and build out the country’s energy sector and economic capacity for the long term. This piece provides a brief analysis of Nigeria’s PIB, highlighting the PIB’s laudable steps while identifying gaps and outlining recommendations for Nigeria to prepare for and seize the opportunity of the energy transition.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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