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Record W2373686939

A Lesson from Canadian" Flow-Through Shares" Policy

2010· article· en· W2373686939 on OpenAlexaboutno aff
Yufei Zhang

Bibliographic record

VenueNatural Resource Economics of China · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessInvestment (military)Mineral resource classificationChinaTax policyPublic policyFinanceStock (firearms)Natural resource economicsGovernment (linguistics)Fossil fuelEconomicsMarket economyEngineeringEconomic growthTax reformWaste management
DOInot available

Abstract

fetched live from OpenAlex

A flow-through share(FTS) is intended to stimulate mineral exploration investment and f inancing via f iscal means in Canada;it is a share of the stock of a mineral resource company where tax deductionsflow through from the company to the investors.This policy is not only applicable to(solid) mineral exploration,but also to oil-gas resources and green resources,which affords a lesson for China's government in the application of public policy relating to sustainable development,and encourages private capital investment.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.095
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0110.006
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0100.001

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 head0.008
GPT teacher head0.260
Teacher spread0.251 · 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
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
Published2010
Admission routes1
Has abstractyes

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