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Record W7117325301 · doi:10.5281/zenodo.17868439

Systemic Discrimination and Racism in the School and Workforce Pathways of Youth with Refugee Experience in Nova Scotia

2025· article· W7117325301 on OpenAlexaffabout
Ifeyinwa Mbakogu, Chana Tikvah Wielinga, Lotanna Odiyi

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRefugeeNova scotiaRacismWorkforceReputationNarrativeIntersectionalityImmigration

Abstract

fetched live from OpenAlex

Although Nova Scotia (NS) has prioritized attracting and retaining newcomers from around the world, there is a paucity of research on the experiences of refugees in the province. In particular, is the minimal research on youth with refugee experience (YRE), considering that approximately half of all refugees are 18 years of age and younger. This paper addresses this gap by presenting findings from research that examines the pre-departure and arrival experiences of 21 youth with refugee experience in Nova Scotia. The paper examines the impact of racism on the resettlement of YREs by presenting the voices and experiential contributions of participants within the enabling framework of critical race theory (CRT). The narratives show that despite fostering a reputation as one of the most welcoming destinations for newcomers, youth with refugee experience often face systemic discrimination and racism, particularly in seeking employment and within educational institutions. The findings provide better understanding of the experiences of YRE, with accessing services and meeting their long-term economic goals that the provincial government, service providers, and researchers may apply to improve the pathways for YRE as they pursue employment in Nova Scotia.

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)0.002
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 score0.581
Threshold uncertainty score0.833

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0030.001
Open science0.0010.005
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 head0.047
GPT teacher head0.304
Teacher spread0.258 · 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
Published2025
Admission routes2
Has abstractyes

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