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Moving, Waiting, Racing: The Emotional and Temporal Experience of Policy for Nurses on Temporary Work Permits in Canada

2021· article· en· W3162410443 on OpenAlexafffundvenueabout
Shiva Nourpanah

Bibliographic record

VenueAnthropologica · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTemporalityEthnographyEmotional laborWork (physics)CredentialSpace (punctuation)SociologyHealth carePolitical scienceNursingPublic relationsPsychologyMedicineSocial psychologyAnthropologyLaw

Abstract

fetched live from OpenAlex

Drawing on ethnographic fieldwork done between April 2015 and August 2016 in Halifax, Canada, with nurses employed on temporary work permits in the healthcare sector in the province of Nova Scotia, Canada, this research contributes to contemporary literature on certain forms of migration temporality and emotionality. I employ policy analysis of credential recognition procedures for nurses and ethnographic research methods to demonstrate how a complex array of intersecting and sometimes contradictory policy contexts in labour, migration and healthcare regulate the movement and work of foreign nurses, including their transition into permanent Canadian residents, and ultimately, citizens, and the lived experienced of this regulation as it extends through time and space.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.418
Teacher spread0.344 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2021
Admission routes4
Has abstractyes

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