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Record W4303982172 · doi:10.17645/si.v10i4.5695

Later‐Life Learning Among Latin Americans in Canada: Toward a Critical Pedagogy of Place

2022· article· en· W4303982172 on OpenAlexaffabout
Shamette Hepburn

Bibliographic record

VenueSocial Inclusion · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsYork University
Fundersnot available
KeywordsLife course approachScholarshipImmigrationMainstreamSociologyLatin AmericansService-learningGender studiesPedagogyEconomic growthPolitical sciencePsychologySocial psychology

Abstract

fetched live from OpenAlex

This article examines interconnections between place‐based education and the Latin American Canadian migratory life course. It presents findings of a grounded theory study that utilized in‐depth interviews of 15 Latin American Canadian immigrant older adults (55 years and older) who participate in a mobile adult day support programme in northwest Toronto. The study explored the experiences of service‐users of place‐based education aimed at developing or strengthening their livelihood strategies. Findings revealed that many ageing immigrants view place‐based education as a vital resource that supports their ability to access culturally specific and mainstream services, expands their social networks, and can boost their life chances at successive life course stages. However, findings also indicated that immigrants also view place‐based education as inadequate and ill‐timed and would have preferred greater access to education when they first settled in Canada. The article contributes to emergent scholarship on ageing, transnational migration, and localized education for settlement and integration. Conceptually, it advances a life course justice approach to racialized immigrants’ later‐life learning by underscoring the utility of integrating a critical pedagogy of place into community education.

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 score0.085
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0270.025
Scholarly communication0.0070.003
Open science0.0020.009
Research integrity0.0010.004
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 head0.029
GPT teacher head0.340
Teacher spread0.310 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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