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Record W4387217535 · doi:10.1177/09721509231196968

The Impact of Remittances on Renewable and Non-renewable Energy Consumption in Jamaica

2023· article· en· W4387217535 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

VenueGlobal Business Review · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsThe King's UniversityWestern UniversityYork University
Fundersnot available
KeywordsRenewable energyConsumption (sociology)EconomicsRemittanceError correction modelEnergy consumptionVector autoregressionShort runCointegrationNatural resource economicsMacroeconomicsEconometricsEconomic growthEngineering

Abstract

fetched live from OpenAlex

Using annual data from 1980 to 2019, we explore the impact of remittance inflows (remittances) on renewable and non-renewable energy consumption in Jamaica. We apply statistically adequate vector error correction and vector autoregression models. There are two primary findings. First, we find that an increase in remittances is associated with a decrease in renewable energy consumption within an error correction model, which suggests a long-run negative relationship between remittances and renewable energy consumption. Second, an increase in remittances is associated with an increase in non-renewable energy consumption in the short run; no cointegrating relationship is detected. One implication of our finding is that Jamaica could strengthen policies that encourage the consumption of renewables while discouraging the consumption of non-renewables. These policies should apply to not only remittance-receiving households but also energy consumers in general to enhance the uptake of renewable energy.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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