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Record W6922234183 · doi:10.11575/prism/40640

Gasoline Pricing in Alberta: Contributing Factors and an Investigation of Policy Alternatives

2022· other· en· W6922234183 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2022
Typeother
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsGasolineExciseSubsidySupply and demandCrude oilInflation (cosmology)Crack spread

Abstract

fetched live from OpenAlex

Gasoline prices in Canada have risen an alarming 57%1 on average since January 2021; Calgary and Edmonton have both faced gasoline price increases of just over 60%2. These increased costs in addition to overall inflation are creating a major financial burden for many Albertans, particularly lower income Albertans. The rise in gasoline prices is primarily due to the rise in the price of crude oil. The price of crude oil has skyrocketed due to Russia’s war in Ukraine, pent up demand from the COVID-19 pandemic and lower than normal inventory levels (USEIA 2022c). The price of gasoline includes not only the cost of crude oil but also of refining it into gasoline, taxes on gasoline and the cost of selling gasoline to consumers. Many provinces in Canada and countries in the world are providing relief to consumers through temporarily lowering or cancelling gasoline excise taxes. Effective April 1, 2022 Alberta temporarily stopped collecting its $0.13/L gasoline excise tax estimated to cost taxpayers $1.3B over three months (Black 2022). Other policy alternatives include letting market forces occur and not doing anything to mitigate high gasoline prices, providing subsidies to vehicle registrants, providing subsidies to low income households and regulating the price of gasoline.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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 designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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