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Record W4402169719 · doi:10.32920/26871334.v1

Canadian Experience Wanted: A Critical Discourse Analysis of Media Representation of Skilled Immigrants

2024· preprint· en· W4402169719 on OpenAlexaffabout
Marta Minta

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsToronto Metropolitan UniversityHumber Polytechnic
Fundersnot available
KeywordsImmigrationRepresentation (politics)Critical discourse analysisSociologyGender studiesPolitical scienceIdeologyPolitics

Abstract

fetched live from OpenAlex

This MRP examines whether and how Canadian English electronic press media represents what is known as 'Canadian experience'. Although Canada is considered an immigrant welcoming country, it has been criticized for its poor recognition of immigrant skills and work experience. The media's portrayal of skilled newcomers reveals underlying social attitudes towards immigrants; this is reflected in contemporary immigration policies and labour market practices, which affect skilled immigrants' integration into Canadian society. Utilizing Critical Discourse Analysis, this study traces the representations of Canadian experience in the national electronic newsprint media, The Globe and Mail, The Toronto Star, and one regional source, the Toronto Sun between 2015-2022. The analysis of the articles reveals how certain skilled immigrants continue to be unfavourably represented by media reporting. The indirect marginalizing discourses embedded within the language of the articles has implications for skilled immigrants in Canada.

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)0.006
metaresearch head score (Gemma)0.015
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 score0.090
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0110.014
Science and technology studies0.0260.016
Scholarly communication0.0160.004
Open science0.0020.005
Research integrity0.0020.003
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 head0.027
GPT teacher head0.403
Teacher spread0.376 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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