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Record W7001504804

A journey beyond the classroom: a narrative inquiry into the settlement struggles of adult EAL students

2015· dissertation· en· W7001504804 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2015
Typedissertation
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeNarrativeSettlement (finance)Government (linguistics)Narrative inquiryEnglish as a second languageEnglish language
DOInot available

Abstract

fetched live from OpenAlex

Canada welcomes and supports refugees from all over the world. However, they encounter many struggles that force them to with withdraw from their English language classes. This Narrative Inquiry explores the lived experiences of two adult refugee students who could not continue with their English classes due to the hardships they encountered. Through research conversations I document their experiences in two narrative accounts, and read across them to find common threads. These common struggles include financial strains, employment, childcare, isolation and mental health. The findings point to the importance of further supporting refugee students in different ways. My recommendations are that ESL teachers develop lessons that include settlement, support services, and Canadian culture information. English language programs need to incorporate support services with professionals trained in ESL, and the different levels of government need to be part of the discussion on how to provide stronger supports through childcare, employment and information accessibility.

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)0.007
metaresearch head score (Gemma)0.008
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 score0.086
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0330.028
Scholarly communication0.0140.008
Open science0.0030.012
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0040.001

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 head0.055
GPT teacher head0.282
Teacher spread0.227 · 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
Published2015
Admission routes1
Has abstractyes

Explore more

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