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Record W3096700696 · doi:10.11575/prism/38349

Settlement and Integration Needs of Skilled Immigrants in Calgary: A Mixed Methods Study

2020· dissertation· en· W3096700696 on OpenAlexaboutno aff
Vibha Kaushik

Bibliographic record

VenuePRISM (University of Calgary) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)ImmigrationMultimethodologyDemographic economicsGeographySociologyEconomicsArchaeologyComputer scienceSocial scienceWorld Wide Web

Abstract

fetched live from OpenAlex

There is a significant body of scholarship on the settlement and integration of immigrants in Canada. However, most knowledge in this domain comes from government and stakeholders’ reports that are based on input from immigrants in general. This information does not focus specifically on skilled immigrants, nor does it include those in the service sector responsible for service provision of this population. Importantly, there is limited academic research available in this domain. Currently, Alberta is experiencing a unique economic climate. Most economic indicators suggest that from 2015 to 2016, Alberta experienced the worst recession in a generation, caused by the steepest and most prolonged oil price shock in Canadian history. Broader economic trends show that the integration of immigrants is affected by the economic conditions they face in their host countries. Further, there is evidence that immigrants who arrive during unfavourable economic conditions experience a permanent disadvantage in integration. Therefore, the settlement and integration of skilled immigrants warrant explicit attention at this critical point in time. Calgary is the largest city in Alberta. Not only do many immigrants arriving in Alberta choose to settle in Calgary, it is also the fourth most sought-after destination for immigrants in Canada. With an increasing number of immigrants arriving in Calgary to work and live, there is a need to better understand how immigrant services in the city support skilled immigrants and contribute to create a positive environment for their settlement and integration in Calgary. The purpose of this study was to understand the settlement and integration needs of skilled immigrants in Calgary and to identify if there are any needs that are not addressed by the services offered by the major immigrant serving agencies in the city. Primarily, the focus of the study was (1) to understand the settlement and integration needs of skilled immigrants in Calgary and (2) to identify if there are gaps in the settlement and integration services for skilled immigrants in Calgary. The study employed a convergent parallel mixed methods design in which qualitative data provided an in-depth exploration of the settlement and integration needs of skilled immigrants in Calgary as understood by immigrant serving agencies in the city, and the quantitative data focused on gaining an understanding about the areas of unmet settlement and integration needs as experienced by skilled immigrants in Calgary. I conducted 10 interviews with immigrant services providers in Calgary to collect qualitative data and analyzed the data using thematic analysis. For the quantitative analysis, I collected 120 survey responses from skilled immigrants who were residents of Calgary and who came to Canada under the Federal Skilled Worker Program. I performed chi-square analysis to reveal any significant relationship between survey items. Findings enhance our understanding of challenges faced by skilled immigrants in Calgary, identify the needs experienced by skilled immigrants in facing those challenges, highlight the gaps in the existing social services, and inform the development and implementation of effective settlement services and programs for skilled immigrants in Calgary.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.292
Teacher spread0.281 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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