MétaCan
Menu
← Back to cohort
Record W4233380349 · doi:10.32920/ryerson.14665359

You're not welcome here: examining the intersections of migration and neoliberal immigration policy in Canada

2021· preprint· en· W4233380349 on OpenAlexaffabout
Rosalind V. Gunn

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsToronto Metropolitan UniversityUniversity of Waterloo
Fundersnot available
KeywordsImmigrationNeoliberalism (international relations)PoliticsImmigration policyPolitical sciencePhenomenonPolitical economySociologyDevelopment economicsLawEconomics

Abstract

fetched live from OpenAlex

This analysis examines the intersections of migration and neoliberal immigration policy in Canada through a political economy lens. It looks particularly at the increasing phenomenon of human smuggling and it asks how the emergence of neoliberalism has shaped Canadian immigration policy and how has this impacted working peoples’ lives and forced them to become migrants. Canada increasingly treats migrants with suspicion and seeks to prevent the less “profitable” ones from entering. Today’s policies are the result of a historical process of entrenching a North-South divide as some sort of unavoidable truth, and the fruits of the global North as requiring protection from “needy” and “lazy” poor in the global South. It is this paradigm which the following analysis seeks to problematize and deconstruct by examining the historical roots of the North-South divide.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0310.011
Scholarly communication0.0120.003
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.067
GPT teacher head0.365
Teacher spread0.299 · 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

Explore more

Same topicEmployment and Welfare Studies→French-language works237,207→