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Record W2235750142

The Wealth of First Nations: An Exploratory Study

2013· article· en· W2235750142 on OpenAlexaffabout
Tom Flanagan, Katrine Beauregard

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProsperityPossession (linguistics)Property rightsIndex (typography)Rule of lawTest (biology)Political scienceDevelopment economicsLawEconomicsEconomic growthPolitics
DOInot available

Abstract

fetched live from OpenAlex

The standard of living of First Nations is on average much lower than that of other Canadians, but some First Nations have achieved higher well-being than others.This paper is an investigation into the factors that promote prosperity for First Nations. We use the Community Well-being Index (CWB), calculated by the Department of Aboriginal Affairs, as a measure of prosperity for First Nations. As possible explanations of differences in well-being, we develop and test four indicators of respect for property rights and the rule of law: use of Certificates of Possession, adoption of property tax, entry into the First Nations Land Management Act, and avoidance of third-party management. In a multiple regression analysis, all four variables are positively correlated with higher CWB scores, even after controlling for cultural background and remoteness of location. Our findings are consistent with comparative and international research that has highlighted the importance of property rights and the rule of law for economic growth.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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 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

Citations5
Published2013
Admission routes2
Has abstractyes

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