MétaCan
Menu
Back to cohort
Record W4414798578 · doi:10.1093/analys/anaf066

Immigrant Selection and Global Subordination: A Critical Response to Sahar Akhtar

2025· article· en· W4414798578 on OpenAlexaboutno aff
Alex Sager

Bibliographic record

VenueAnalysis · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSelection (genetic algorithm)ImmigrationSelection bias

Abstract

fetched live from OpenAlex

In 1908, the Canadian government passed a law to prevent immigration from British India, making the right to immigrate conditional on completing a continuous journey from the country of origin. Hundreds of thousands of European immigrants easily met this stipulation; doing so was nearly impossible for British Indians. In April 1914, Canadian authorities in Vancouver, British Columbia detained 376 British Sikh, Muslim and Hindu subjects travelling on the Japanese steamship Komagata Maru from the Punjab. The Komagata Maru incident, as it has come to be known, reminds us of the toxic role of immigration policy in promulgating anti-Asian racism in the Americas. Immigrant selection has long been a mechanism for nation building, in which the nation has been understood in racial and ethnic terms (FitzGerald and Cook-Martín 2014). Selection by race, ethnicity and religion is by no means a relic of the distant past. The notorious White Australia policy endured until 1966. Until the passage of the 2000 Citizenship Law, Germany provided easy access to citizenship for people of German descent but limited opportunities to naturalize even for children of immigrants born in Germany. Liberia continues to restrict citizenship to ‘persons who are Negroes or of Negro descent’ (1984 Constitution of the Republic of Liberia, Article 27).

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
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 head0.006
GPT teacher head0.346
Teacher spread0.340 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAnalysisSame topicMigration and Labor DynamicsFrench-language works237,207