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Record W2473353267

Charitable Gifts of Conservation Easements: Lessons from the US Experience in Enhancing the Tax Incentive

2011· article· en· W2473353267 on OpenAlexaffabout
Ellen B. Zweibel, Karen Cooper

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEasementIncentivePublic economicsTax deductionTax creditBusinessTax incentiveEconomicsTax reformNatural resource economicsFinanceState income taxPolitical scienceMarket economyGross incomeLaw
DOInot available

Abstract

fetched live from OpenAlex

In Canada, the Income Tax Act provides favourable capital gains treatment for gifts of full and partial interests in ecologically sensitive land made to eligible conservation charities, municipalities, and federal and provincial governments through the ecological gifts program (EGP). Such donations increasingly take the form of conservation easements – binding agreements between landowners and conservation organizations that permanently restrict land development or create affirmative obligations in favour of specific conservation objectives. This article compares key features of the current Canadian and US tax incentives for donations of conservation easements with a view to considering whether Canada’s EGP should expand its current provisions to include some US features aimed at increasing donations from “land-rich and cash-poor” taxpayers. These features include transferable tax credits, longer carry forward periods, the possibility of carrybacks, limited refundable tax credits, and intergenerational transfers of unused charitable credits.

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)0.011
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 score0.962
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.005
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.097
GPT teacher head0.237
Teacher spread0.140 · 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

Citations2
Published2011
Admission routes2
Has abstractyes

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