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Record W4235931835 · doi:10.32920/ryerson.14663571

Low-skilled temporary foreign workers in Canada : how their subordinate status is discursively legitimated through public opinion

2021· preprint· en· W4235931835 on OpenAlexaffabout
Carol Lilian Boate

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsToronto Metropolitan UniversityMcGill UniversityYork University
Fundersnot available
KeywordsPublic opinionDominance (genetics)Political sciencePopulationPower (physics)Public discourseOrder (exchange)Public relationsSociologyPoliticsBusinessLaw

Abstract

fetched live from OpenAlex

This paper attempts to show how public opinion discursively legitimates the subordinate status that low-skilled temporary foreign workers are assigned in Canada. The author first shows how this status has been created through the Temporary Foreign Worker Program and, more specifically, the Pilot Project for Occupations Requiring Lower Levels of Formal Training. In order to analyze public opinion, comments made online in reference to news outlet articles concerning low-skilled temporary foreign workers were located. Using a dual labor market theoretical framework a critical discourse analysis is performed on these comments, attempting to uncover how power and dominance are reproduced within them. The results of this analysis demonstrate how the discourse contained within public opinion helps to maintain the current status faced by this population.

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)0.010
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 score0.061
Threshold uncertainty score0.442

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0190.016
Scholarly communication0.0100.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.280
Teacher spread0.244 · 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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