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Record W2262303837 · doi:10.5663/aps.v5i2.25351

Families in Transition: The Impact of Family Relationships and Work on Mobility Patterns of Aboriginal People Living in Urban Centres across Canada

2016· article· en· W2262303837 on OpenAlexaffvenueabout
Jacqueline M. Quinless, Ricardo Manmohan

Bibliographic record

Venueaboriginal policy studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsRoyal Roads UniversityUniversity of Victoria
Fundersnot available
KeywordsSocioeconomic statusGeographyDemographic economicsMeaning (existential)Social mobilityDemographySurvey data collectionPath analysis (statistics)PsychologySociologySocioeconomicsGerontologyMedicinePopulationEconomicsSocial science

Abstract

fetched live from OpenAlex

The present analysis makes use of data taken from the public use micro data file (PUMF) from the 2012 Aboriginal Peoples Survey (APS) to examine the effects of various socioeconomic factors such as age, sex, education level, family composition (expressed by the number of children in the household), and total personal income on the mobility patterns of Aboriginal people living off-reserve across Canada. Two separate path analyses were conducted to evaluate critically the decomposition effects that these variables have on mobility. The results of the path analysis show that age is inversely related to mobility, meaning younger people move more frequently. However, contrary to other studies, this research analysis shows that age becomes less significant when we consider that people with higher levels of education are indeed more mobile than others, although the strength of this effect is actually mediated through personal income and family composition.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.359
Teacher spread0.335 · 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 designQualitative
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

Citations3
Published2016
Admission routes3
Has abstractyes

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