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Record W2124585185 · doi:10.14430/arctic4481

Monetary Poverty in Inuit Nunangat

2015· article· en· W2124585185 on OpenAlexaffvenueabout
Gérard Duhaime, Roberson Édouard

Bibliographic record

VenueARCTIC · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPovertyGeographyCensusPoverty rateScope (computer science)ArcticEmic and eticLow incomeEconomicsSocioeconomicsEconomic growthDemographySociologyPopulationEcology

Abstract

fetched live from OpenAlex

This article measures for the first time the scope of poverty in Inuit Nunangat, the four regions of the Canadian Arctic where Inuit people live. On the basis of a monetary definition of poverty, we propose and apply a method adapted to key characteristics of the Inuit condition. For each region, we developed a low income measure (LIM) that takes household composition and consumer prices into account, using data from the master file of the 2006 Census of Canada and surveys by Aboriginal Affairs and Northern Development Canada on the Revised Northern Food Basket. For Inuit Nunangat as a whole, the low income measure was $22 216 and the low income rate (LIR) was 44%. Values vary among regions: in Nunavik, for example, the low income rate is 37.5%. However, throughout Inuit Nunangat, poverty rates are significantly higher than those observed in Canada. We recommend further statistical exploration to better identify not only the factors correlated with households living in poverty, but also a qualitative approach to produce an Inuit emic perspective. Both tools are necessary for informed policy to fight against poverty.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.062
GPT teacher head0.365
Teacher spread0.303 · 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.

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

Citations18
Published2015
Admission routes3
Has abstractyes

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