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Record W346206013

The Effects of Personal Characteristics on Migration from Prairie Cities to First Nations

2002· article· en· W346206013 on OpenAlexvenueaboutno aff
Martin Cooke

Bibliographic record

VenueCanadian ethnic studies · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyInternal migrationHuman migrationHuman capitalWelfare economicsPolitical sciencePopulationDemographySociologyEconomicsEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT/RESUME While it has been known for some time that there is a considerable amount of migration from Canadian cities to reserves, this migration has been overshadowed in the literature by movement from reserves into the city. Migration to reserves is largely seen as the result of a failure to adapt to urban life. This paper describes an attempt to relate individual demographic and human capital characteristics to migration of Registered Indians to Manitoba, Saskatchewan, and Alberta reserves between 1986 and 1991, using 1991 Aboriginal People Survey data and logistic regression models. The relationships found between human capital variables and mobility are less clear than human capital models predict. However, an interaction of the effects of gender and education on the probability of having moved to a reserve suggests that labour markets in reserve communities play a role in the different migration patterns of men and women. Approaches considering the pull of reserves in addition to pushes from cities are encouraged in order to present a more complete picture of migration. INTRODUCTION Bien que nous connaissions depuis longtemps que le taux de migration des villes vers les reserves est plutot eleve, celui-ci est eclipse dans la litterature par Ia migration des reserves vers les villes. Souvent, l'on considere que Ia migration vers les reserves est causee par une incapacite de s'adapter a Ia vie urbaine. Cet article tente de relier Ia migration des Indiens inscrits vers les reserves du Manitoba, de Ia Saskatchewan et de l'Alberta entre les annees 1986 et 1991 aux caracteristiques demographiques individuelles et aux caracteristiques de capital humain. Les donnees de L'Enquete aupres des peuples autochtones en 1991 ainsi que des modeles de regression logistique sont utilises. Les relations trouvees entre les variables de capital humain et de mobilite sont moms evidentes que celles prevues par les modeles de capital humain. Cependant, I'influence du sexe et de l'education sur la probabilite d'avoir demenage la reserve suggere que les marches de travail dans les reserves ont un impact sur les di fferentes tendances de migration chez les hommes et les femmes. Dans le but de fournir une representation plus complete de lamigration, nous encourageons l'utilisation d'approches qui prennent en consideration les aspects positifs des reserves de meme que les aspects negatifs des villes. The growth of the urban Aboriginal population has perhaps been the most important change in the demography of Canadian Aboriginal people since the 1950s. As Peters (1996) describes it, academic and popular writing about urbanization has constructed the process as both a problem for cities, and as a response and a potential solution to poverty on reserves. Almost universally, the belief has been that the urban Aboriginal population has grown as a direct result of movement from reserve communities into cities, undertaken in order to find employment or to escape poor social conditions. This view was perhaps most clearly articulated by the Hawthorn Report, which preceded the now infamous 1967 White Paper, and which claimed that much of the poverty in Aboriginal communities was intractable and that the best solution was for migration to cities to be encouraged (Hawthorn et al. 1966:256). In the 1970s and 1980s, several studies were produced that described the difficulties faced by Aboriginal people once i n the city (Brody, 1971; Denton, 1972; Clatworthy, 1980; Clatworthy and Hull, 1983). According to these studies, racism and a lack of marketable skills and education contribute to high unemployment and dependence on social assistance in the city. Life in the city is often made more difficult by poor social conditions in the low-income areas in which many Aboriginal people find the only affordable housing (Williams, 1997; Barsh, 1997). Social services delivered along a dominant-culture model give Aboriginal people little support for adjustment to the urban setting (Reeves and Frideres, 1981). …

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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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.064
GPT teacher head0.321
Teacher spread0.257 · 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 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

Citations13
Published2002
Admission routes2
Has abstractyes

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