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Record W2335902049 · doi:10.18584/iipj.2016.7.2.2

Life Satisfaction among Aboriginal Peoples in the Canadian Prairies: Evidence from the Equality, Security and Community Survey

2016· article· en· W2335902049 on OpenAlexafffundvenueabout
Christopher Barrington‐Leigh, Sabina J. Sloman

Bibliographic record

VenueInternational Indigenous Policy Journal · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaAboriginal Affairs and Northern Development CanadaIndigenous and Northern Affairs Canada
KeywordsLife satisfactionIndigenousGeographyQuality of life (healthcare)SocioeconomicsSurvey data collectionPopulationGeneral Social SurveyPsychologyEconomic growthSociologyDemographySocial psychologyEconomicsEcology

Abstract

fetched live from OpenAlex

Subjective measures of overall quality of life are built in to numerous surveys in Canada and around the world, and are increasingly analyzed and used as indicators of human well-being and social progress. Yet, even in Canada, federal surveys exclude Aboriginal peoples on-reserve and, in general, there are very few data sources on life satisfaction among Aboriginal respondents. We report on two exceptional surveys that do solicit life satisfaction assessments from Aboriginal respondents, and compare inferences from these data to the general Canadian population. We generally find comparable effects of objective life circumstances for the two groups, and use these to explain some of the advantages and disadvantages affecting life satisfaction in each sample. On the other hand, we find an unusual coefficient on the survey income measure for on-reserve Aboriginal respondents, likely indicating that total income is not appropriately measured by the standard income question. We propose that policy interest in life satisfaction measures for gauging effective avenues for improving lives is appropriate in the case of Aboriginal groups in Canada, just as for other populations in Canada and around the world.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.077
GPT teacher head0.406
Teacher spread0.329 · 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

Citations23
Published2016
Admission routes4
Has abstractyes

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