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Rationalizing the Canadian Income Tax System

2019· article· en· W2979838046 on OpenAlexaffvenueabout
Robin Boadway

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsQueen's University
Fundersnot available
KeywordsTax reformValue-added taxIndirect taxTax creditPublic economicsAd valorem taxState income taxDirect taxTax avoidanceBusinessDouble taxationEconomicsEconomic policy

Abstract

fetched live from OpenAlex

The Canadian tax system is based on principles informed by the Carter report, and these principles have been challenged as circumstances have changed and ideas about tax policy have evolved. The personal tax system pays only lip service to the comprehensive income tax ideal, and the corporate tax is designed as a complement to a comprehensive tax system that does not exist. Canadian policy makers face the unprecedented challenges of (1) globalization, (2) an economy increasingly based on services and technology, and (3) growing inequality of income, wealth, and opportunity. Modern principles of tax design are reflected in recent tax reform proposals recommended by the Mirrlees review in the United Kingdom. Major tax reforms have been undertaken in other member countries of the Organisation for Economic Co-operation and Development. Some piecemeal innovations in tax policy have been implemented in Canada, such as registered retirement savings plans, tax-free savings accounts, the goods and services tax/harmonized sales tax, and refundable tax credits, but these measures have not been coordinated. The corporate tax structure has changed only modestly. This paper explores options for feasible reform of the Canadian tax system that might enhance equity and efficiency.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.271
Threshold uncertainty score0.845

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0150.009
Scholarly communication0.0110.003
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2019
Admission routes3
Has abstractyes

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