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Record W2884600613 · doi:10.1017/s1355770x18000281

The impact of oil revenues on wellbeing in Chad

2018· article· en· W2884600613 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironment and Development Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsUniversité Laval
FundersDepartment for International DevelopmentInternational Development Research CentreGovernment of Canada
KeywordsRevenueDisadvantagedRedistribution (election)Government revenueTotal revenueBusinessEconomicsGovernment (linguistics)Public economicsAgricultural economicsEconomic growthFinancePolitical sciencePolitics

Abstract

fetched live from OpenAlex

Abstract This paper uses two recent household surveys, together with data from the College for Control and Monitoring of Oil Revenues, to analyse the impact of oil revenues on wellbeing in Chad. Following a multiple-correspondence analysis to estimate a synthetic household-based multidimensional wellbeing (MDW) index, we used the difference-in-difference approach to assess the impact of oil revenues on average MDW at the department level. We found evidence that departments in Chad that received significant oil transfers have a higher MDW compared to those disadvantaged by the oil-revenue-redistribution policy. We conclude that, in order to promote economic inclusion, the government of Chad should better develop oil-revenue-redistribution policies according to local development needs and target the poorest departments.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.596

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 integrity0.0000.000
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 head0.018
GPT teacher head0.198
Teacher spread0.180 · 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