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Policy Forum: In Defence of the First Nations Fiscal Management Act

2021· article· en· W3213369703 on OpenAlexvenueaboutno aff
André Le Dressay

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLegal and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJurisdictionIndigenousTaxpayerSupreme courtDebtBusinessPublic administrationPolitical scienceLawFinance

Abstract

fetched live from OpenAlex

The debate with respect to the recognition of Indigenous rights, title, and jurisdiction has largely been won. It has now moved to how best to implement those rights, title, and inherent jurisdictions. For Indigenous taxation jurisdiction, implementation must address challenges related to taxpayer representation, concurrent jurisdiction, service agreements with other governments, administrative capacity, financial management, and access to public debt capital at competitive rates. In this article, the author argues that the First Nations Fiscal Management Act (FMA) has been successful in overcoming these challenges. The FMA has protected and expanded Indigenous tax jurisdiction through standards and institutional support. As a result, it represents an effective path for interested Indigenous governments "to exercise [their] inherently governmental power of taxation" affirmed by the Supreme Court of Canada in Matsqui Indian Band, and to expand their use of that power.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.473
Threshold uncertainty score0.952

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.003
Scholarly communication0.0120.004
Open science0.0030.003
Research integrity0.0310.013
Insufficient payload (model declined to judge)0.0170.006

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 head0.015
GPT teacher head0.178
Teacher spread0.163 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2021
Admission routes2
Has abstractyes

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