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Record W2586592213 · doi:10.20355/c5cs3s

Pursuit of the Red Passport: Perceptions of Global Citizenship Among Low-paid Global Workers

2017· article· en· W2586592213 on OpenAlexfundvenueaboutno aff
Whitney Haynes

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsCitizenshipContext (archaeology)Global citizenshipOrder (exchange)Freedom of movementImmigrationPolitical sciencePerceptionPolitical economyDevelopment economicsSociologyEconomicsLawPoliticsGeography

Abstract

fetched live from OpenAlex

The movement of people around the world for the sole purpose of their labour has existed for hundreds of years and is at the root of a growing capitalist regime. Today, millions of people, particularly from low-income countries, are forced to move without their families across borders to high-income countries in order to send home remittances to help their families survive. The control of their global movement is based on a system of borders and visa regulations, where their passports, determined by their citizenship, offer very limited global mobility. This article explores the current context of low-paid labour migration in relation to global citizenship and global mobility rights. Workers interviewed in Canada, parts of Europe and Asia (n=24) describe their quests for the freedom of global mobility and navigating citizenship systems in order to obtain a strong passport/citizenship, also known as the “red passport.” The fight for the red passport and the right to global mobility is linked to their understandings of true global citizenship.

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)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.280
Teacher spread0.267 · 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
Published2017
Admission routes3
Has abstractyes

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