MétaCan
Menu
Back to cohort
Record W4408797747 · doi:10.32920/28646312.v1

Homestays can help refugee women get to grips with life in a new country

2025· preprint· en· W4408797747 on OpenAlexaboutno aff
Areej Al‐Hamad, Kateryna Metersky

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeePolitical sciencePsychologyLaw

Abstract

fetched live from OpenAlex

<p>[para. 1-3]: "According to the United Nations High Commissioner for Refugees, more than 117 million people are displaced worldwide. Many of those displaced from their homes are women and girls. In 2020, women and girls constituted about 46 per cent of the refugees who were resettled in Canada.</p> <p>Women and girls often contend with unique challenges from being displaced. There is a crucial need to understand the gender-specific challenges and issues they face. As global displacement grows, the stories of those seeking refuge need to be heard and understood, not just to enhance their lives but also to enrich our communities.</p> <p>Our research focuses on the homestay experiences of Ukrainian refugee women in the Greater Toronto Area. We explore how thoughtful, inclusive homestay programs can make a significant difference in women’s lives."</p>

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.884
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicMiddle East and Rwanda ConflictsFrench-language works237,207