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Record W4230758159 · doi:10.32920/ryerson.14664765.v1

Community-School Partnerships: Assisting Newcomer Youth In Montreal

2021· preprint· en· W4230758159 on OpenAlexaffabout
Yamie Tremblay

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsChristian ministrySettlement (finance)Political scienceImmigrationPublic relationsSociologyPublic administrationBusiness

Abstract

fetched live from OpenAlex

As universal and mandatory institutions, schools are the first institutional frame of reference newcomer youth encounter upon their arrival in Canada, and as such they play a central role in their settlement process. Although the Quebec Ministry of Education provides guidelines regarding the integration of immigrant students into Quebec educational institutions, some secondary schools in Montreal seem unprepared to respond to theunique needs of newcomer youth.This qualitative case study involving six key informantsreveals that schools need experts from community organizations who have a greater capacity to assist youth in their settlement experiences. However, partnering between school and community organizations are often based on difficult and unequal relationships which have a negative impact on the programs and services offeredto newcomer students. It is crucial that the various ministries involved in the well-being of youth provide long-term funding for collaborative programs targeting newcomers. This could fortify programs that are already implemented, encourage new initiative, and spread them to educational institutions around the province.

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)0.003
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 score0.308
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.006
Scholarly communication0.0040.002
Open science0.0030.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.156
GPT teacher head0.388
Teacher spread0.233 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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