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Record W4236325113 · doi:10.32920/ryerson.14647362

Challenges of internationally educated Filipino social work professionals : implications for social work practice in Canada

2021· preprint· en· W4236325113 on OpenAlexaffabout
Roshena Grace Hernandez

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsToronto Metropolitan UniversityCentre for Social Innovation
Fundersnot available
KeywordsSocial workInsiderLegislationWork (physics)Public relationsQualitative researchSociologySocial WelfarePolitical scienceWelfareSocial science

Abstract

fetched live from OpenAlex

This study explores the lived experiences of internationally educated, Filipino social work professionals during their integration into the Canadian labour force. The need to pursue this topic stemmed from the recognition of the barriers faced by internationally educated Social Work professionals as they embark on a social work career in Canada. This phenomenological, qualitative research utilized one-on-one in-depth interviews with four Filipino social work professionals who obtained education and professional experience in the Philippines. Participants have all resided within Canada for five to ten years, have had their credentials assessed, and have been registered with Ontario’s regulatory body. As an insider of this particular group, the researcher aims to identify the challenges they encounter to pursuing a Canadian social work career, which are limited by systemic barriers; a lack of connections; personal barriers; and a lack of knowledge regarding Canadian legislation and the social welfare system.

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)0.004
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 score0.092
Threshold uncertainty score0.665

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0550.014
Scholarly communication0.0120.003
Open science0.0030.011
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.115
GPT teacher head0.455
Teacher spread0.340 · 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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