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Record W2946632169 · doi:10.25071/1913-9632.39366

Labouring for Citizenship

2019· article· en· W2946632169 on OpenAlexvenueno aff
Michael Sullivan

Bibliographic record

VenueLeft History An Interdisciplinary Journal of Historical Inquiry and Debate · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationCitizenshipSolidarityPolitical scienceEnforcementPolitical economyImmigration policyGovernment (linguistics)Ethnic groupSociologyLawPolitics

Abstract

fetched live from OpenAlex

This article draws from the lessons of the Mexican-American labour movement’s internal conflict during the twentieth century about how to respond to new co-ethnic migration to consider what new immigrants and citizens owe to one another as workers in the current US immigration reform debate. For much of the twentieth century, Mexican-Americans were divided about how the US government should respond to new unauthorized and temporary legal immigration from Mexico. Though their class interests diverged, Mexican-American business and union leaders joined forces to lobby for border security and increased immigration enforcement. During the same period, progressive Mexican-American labour leaders advanced a countervailing message of transnational solidarity between newcomers and their settled immigrant compatriots. They further demanded that all Americans recognize the earned citizenship of immigrants who contributed to their families, communities and adopted nation through their labour.

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)0.003
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.018
Scholarly communication0.0070.005
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0150.002

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 head0.061
GPT teacher head0.337
Teacher spread0.276 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueLeft History An Interdisciplinary Journal of Historical Inquiry and DebateSame topicMigration, Ethnicity, and EconomyFrench-language works237,207