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Record W2959984840

Examining the lived experiences of integration by refugees residing in Winnipeg, Manitoba

2018· dissertation· en· W2959984840 on OpenAlexaboutno aff
Maja Aziraj

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeGerontologyGeographyPolitical scienceSociologyGender studiesMedicineArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines the integration experiences of refugees in Winnipeg, Manitoba. Using Berry’s acculturation model and Social Capital theory, this research aims to gain a critical understanding of the challenges facing these newcomers during their integration experiences. This research used qualitative methods through semi-structured interviews with three participants. Results have shown that that the pathway to integration is not fixed, but rather fluid and may change over time. Findings indicate that forming social networks with the larger Canadian society and within faith/cultural groups are significant factors to refugees’ feelings of integration. This study suggests that social programs and refugee services in Winnipeg create opportunities for networking and collaboration amongst each other by sharing information, new innovations and best practices. It is also suggested that social programs and refugee services should also support the Canadian society in its process of adaptation to newcomers.

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)0.003
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0200.011
Scholarly communication0.0050.002
Open science0.0020.008
Research integrity0.0010.002
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 head0.034
GPT teacher head0.284
Teacher spread0.249 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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