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Record W7132877893

Multiculturalism Policies: Identifying the Dialectic of the "Ideal Type" within the Practices of Canadian Nursing

2014· dissertation· W7132877893 on OpenAlexaffabout
Nadia Prendergast

Bibliographic record

VenueTSpace · 2014
Typedissertation
Language
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDialecticMulticulturalismFeminismIdeal (ethics)ColonialismRacismIntersectionalitySnowball sampling
DOInot available

Abstract

fetched live from OpenAlex

Since Canada's first multiculturalism policy in 1971, there has been an influx of Internationally Educated Nurses (IENs) of colour to Canada. Studies show IENs occupying low-paid menial positions, while being excluded from policy-making leadership positions. Colonial values currently function through the notion of the "ideal type", a term defined as a nurse who is white, middle class and occupying policy-making leadership roles. Within Canadian nursing, there appears to be a dialectic relationship between multiculturalism policies and the ideal type that become camouflaged by the term I have identified as the "hybrid space." The hybrid space consists of public health nurses, clinicians, clinical case coordinators, and unit leaders who are registered nurses that work on the front-line with minimal leadership responsibilities. Although these nurses have comparable qualifications as their Canadian-born counterpart, they are not groomed into policy making leadership roles, but rather remain fixed in the hybrid-space. Through the experiences of IENs, this study shows how the dialectic relationship helps in maintaining Canada's favourable position within the global market. Post colonial theory, antiracist feminism and Black Canadian feminist thought were used as theoretical frameworks to expose issues of racism and inequalities within the hybrid space. In-depth interviews, a qualitative methodology, explored the experiences of these IENs in the hybrid space. Ten IENs of colour who were from the United Kingdom and the ex-British colonies (India and the Caribbean) were recruited using the snowball method. The research uncovered several major themes such as, Non-Recognition, No Leaders of Colour at the Top, Faith and Spirituality and Valuing Their Heritage. The themes were divided into two further categories: 1) Challenges and 2) Resistance. Although the hybrid space was challenging, the IENs used these barriers as spaces of resistance in order to survive.

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)0.019
metaresearch head score (Gemma)0.020
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 score0.159
Threshold uncertainty score0.976

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0490.069
Scholarly communication0.0200.008
Open science0.0030.013
Research integrity0.0020.006
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 head0.094
GPT teacher head0.452
Teacher spread0.358 · 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
Published2014
Admission routes2
Has abstractyes

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