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Record W3018416602 · doi:10.1111/opec.12168

The Presidential Amnesty Programme of 2009 and Nigerian Oil Production: a disaggregate econometric analysis

2020· article· en· W3018416602 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOPEC Energy Review · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAmnestyPresidential systemRevenueEconomicsProduction (economics)SurrenderPolitical scienceFinancePoliticsLawMacroeconomics

Abstract

fetched live from OpenAlex

Abstract We analyse the impact of the Presidential Amnesty Programme on crude oil production in Nigeria. The President of Nigeria instituted an amnesty programme in June 2009 to end the disruptive protests in the oil‐producing Niger Delta. Between 2006 and 2009, it is estimated that crude oil production losses exceeded 650,000 barrels per day, dramatically reducing government revenue. The amnesty programme provided militants a state pardon, educational training and a monthly stipend in exchange for the surrender of weapons. In this research, we use disaggregate oil‐well‐level data to estimate a difference‐in‐difference model of Nigerian crude oil production. The estimates reveal that the Presidential Amnesty Programme increased the oil output in the Niger Delta by about 40 per cent above the level that would have been achieved in the absence of the policy.

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.

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: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.204
Teacher spread0.174 · 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