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Record W1606624811 · doi:10.55016/ojs/sppp.v5i1.42375

Departures From Neutrality in Canada’s Goods and Services Tax

2012· article· en· W1606624811 on OpenAlexaffabout
Michael Smart

Bibliographic record

VenueThe School of Public Policy Publications · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeutralityGoods and servicesBusinessEconomicsCommerceEconomyPolitical scienceLaw

Abstract

fetched live from OpenAlex

With recent accessions to the federal-provincial Harmonized Sales Tax, provinces with valueadded taxes (VATs) now comprise over two-thirds of the national economy. While Canadian VATs are economically superior to the taxes they replaced, they are not as well designed as in other countries. An efficient VAT is a uniform tax on all consumer (but not business) purchases. Although the OECD has reported that Canada’s VAT is one of the most efficient in the world, that assessment was based on data shown here to be misleading. In reality, Canada’s VATs have large exemptions, rebates and rate preferences that reduce revenues and hamper productivity. If all these tax preferences were eliminated, government VAT revenues would increase by as much as $39 billion, or more than 50 percent. Moreover, taxing consumer commodities at a single rate reduces opportunities for tax evasion, simplifies tax compliance, and in most cases increases economic productivity. Given the fiscal and productivity challenges currently facing Canadian governments, a new look at VAT design is clearly warranted. This paper offers a detailed assessment of the effects of the tax on the economy, and it proposes a number of specific, feasible reforms to the GST-HST system.

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)0.001
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 score0.591
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.032
GPT teacher head0.308
Teacher spread0.276 · 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

Citations8
Published2012
Admission routes2
Has abstractyes

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