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Record W2785803927

Equity in Policy: Failure and Opportunity

2010· article· en· W2785803927 on OpenAlexaboutno aff
Henry J. Vaux

Bibliographic record

VenueUNM’s Digital Repository (University of New Mexico) · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)BusinessPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

The preoccupation of economists with matters of efficiency helps to explain why matters of economic equity have been neglected.Further, the fact that desirable patterns of equity cannot be identified scientifically constrains economists from making normative judgments about equity.The fact that policymakers are frequently disinterested in equity matters means that economists tend to look elsewhere within their field for interesting questions to pursue.Two case study examples illustrate how the resolution of equity issues can be joined with solutions to other water management problems.The first case study, Northern Voices, focuses on the making of land and water policy in an area at considerable risk from the development of the Alberta, or Athabasca, tar sands and other upstream mining.Policy options which acknowledge, rather than ignore, the preferences of First Nations aboriginal peoples of the Northwest Territories would protect environmental assets which provide significant environmental services for all residents of the Western Hemisphere.The second case study concerns the Colorado River, and exemplifies the problems of over-allocated river basins.Recent experience shows that conventional negotiating processes are unlikely to lead to reductions in water allocations.The significant claims of Native Americans to the waters of the Colorado could be settled and over-allocation managed by awarding basin tribes rights to much of the Colorado River and authorizing them to auction water to the highest bidder through a Colorado River Water Exchange.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.309
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.033
GPT teacher head0.221
Teacher spread0.188 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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