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Record W4391658429 · doi:10.32920/25193501.v1

Political Capital, the COVID-19 Pandemic, and Pathways to Permanent Residency for Low-Skilled Migrant Workers: A Bourdieusian Perspective

2024· preprint· en· W4391658429 on OpenAlexafffundabout
Hayley Cuthbertson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan University
FundersStrongPublic Health Agency of Canada
KeywordsImmigrationPandemicCitizenshipPoliticsCoronavirus disease 2019 (COVID-19)Political scienceHuman capitalPerspective (graphical)RefugeeDemographic economicsPower (physics)SociologyCapital (architecture)Labour economicsEconomic growthEconomicsMedicineLawGeographyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has had a swift and dramatic impact on every aspect of Canadian life. This paper explores how the socio-economic effects of the COVID-19 pandemic have altered the positionality of low-skilled migrant workers in the Canadian immigration regime and labour market. Using Pierre Bourdieu’s sociological framework and concept of political capital, this paper seeks to explain how low-skilled migrant workers temporarily benefited from the distinction they received as essential workers during the pandemic in the form of new, albeit temporary, pathways to permanent residency. The designation of “essential” provided to low-skilled migrants and the distinction that accompanied it allowed them to experience an increased accumulation of political capital and redistribution of influential power. This paper will examine the Temporary Residency to Permanent Residency Pathway and Guardian Angel Program as examples of the fluctuations in Immigrant, Refugees and Citizenship in Canada’s practices during the pandemic and as temporary public policy responses to the increase in political capital accumulated by low-skilled migrant workers.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.030
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.045
GPT teacher head0.375
Teacher spread0.330 · 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 designNot applicable
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
Published2024
Admission routes3
Has abstractyes

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