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Record W4250913836 · doi:10.32920/ryerson.14663877

The Newcomer Women of Aliddesa: Exploring Practices of Resettlement, Citizenship, and Community Development in Toronto

2021· preprint· en· W4250913836 on OpenAlexaffabout
Shelley Marie Hasho

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsCitizenshipSociologyGender studiesCommunity developmentPolitical scienceEconomic growthLawPolitics

Abstract

fetched live from OpenAlex

This qualitative and exploratory research project focuses on observing Aliddesa, a grassroots organization that is made up of Spanish speaking newcomer women based in Toronto. Via interviews, personal reflections in writing, and a focus group with three members of Aliddesa, research findings provide insight into the participant’s personal experiences of resettlement and their perceptions about community development work. Research recommendations point to the value of reconceptualising the resettlement process by documenting the real life stories of newcomer women, and also, by developing a model of resettlement that more acutely describes this process with issues of gender as the primary focus. In addition, research findings are analysed from a conceptual framework of cultural citizenship theory, suggesting that it is a relevant paradigm to discuss and highlight the contributions that are made by newcomer women and also the benefits that enrich Canadian society as a result of their activities.

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)0.003
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 score0.068
Threshold uncertainty score0.492

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0230.011
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.155
GPT teacher head0.350
Teacher spread0.195 · 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
Published2021
Admission routes2
Has abstractyes

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