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Record W2766813362

A Bridge to Where? An Analysis of the Effectiveness of the Bridging Programs for Internationally Trained Professionals in Toronto

2017· dissertation· en· W2766813362 on OpenAlexaboutno aff
Abdulhamid Hathiyani

Bibliographic record

VenueTSpace (University of Toronto) · 2017
Typedissertation
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBridging (networking)Bridge (graph theory)EngineeringEngineering managementComputer scienceMedicineComputer security
DOInot available

Abstract

fetched live from OpenAlex

The biggest hurdle for new immigrants in Canada is their integration into the economic system. These immigrants have higher levels of education but their earnings have been lower and falling in comparison to the native-born Canadians (Akter et al., 2013; Block and Galabuzzi, 2011; Reitz, 2011). The issue of integrating Internationally Educated Professionals (IEPs) into the labour market in Canada is complex and multifaceted. In its effort to ease this gap of integration, the provincial government has invested millions of dollars to establish numerous â bridging programsâ in Ontario. These bridging programs that are supposed to integrate IEPs quickly into the labour market vary depending on the profession, service providers, their length and structure. Utilizing qualitative research and an interpretivist lens, with the help of IEPs (n=20) who have completed the bridging programs and service providers (n=8) for primary data, it has become apparent that although these programs were of benefit to some participants, they do not live up to expectations for many IEPs who continue to struggle to get employed in their profession. This thesis identifies neoliberalism, as not only an economic and political force but also a potent ideology that fosters self-blame.The bridging programs are short-term courses of varying lengths that are supposed to help IEPs address and overcome the challenges of economic integration. They may help in certain ways but are neither equipped to address, nor capable of addressing, the systemic issues of discrimination or racism, with issues of inconsistencies, instability and short sidedness surrounding them. An overall change in attitude to embrace social responsibility and renewed commitment to social justice is required by all stakeholders, if we are to address the ongoing plight of the so many IEPs who are qualified and skilled, but cannot practice in their professions.

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)0.005
metaresearch head score (Gemma)0.019
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 score0.904
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0090.002
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.423
Teacher spread0.389 · 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
Published2017
Admission routes1
Has abstractyes

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