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Record W4283706358 · doi:10.1080/13621025.2022.2091228

Precarious legal status trajectories as method, and the work of legal status

2022· article· en· W4283706358 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCitizenship Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitizenshipLegal statusContext (archaeology)JurisdictionSociologyWork (physics)Inclusion (mineral)Political scienceLawLaw and economicsCriminologyGender studiesPoliticsGeography

Abstract

fetched live from OpenAlex

Critiques of 'fantasy citizenship' include calls to migrantize the citizen and denationalize citizenship and migration studies. In response, this essay proposes 'precarious legal status trajectories (PLSTs) as method', with a focus on the work of legal status. This approach captures changes in sociolegal status trajectories, including illegalization, and builds a 'thicker' approach to trajectories. The work of status refers to effort, time, money, and other resources devoted to being present in a jurisdiction, and/or gain access to services and protections. The approach also considers work that does not produce changes and is not counted, and interactions with other actors. This contributes to understanding how precarious legal status trajectories are assembled and contribute to inequalities in citizenship and dynamics of differential inclusion. It migrantizes the citizen in a context where the share of citizens who were precarious noncitizens continues to rise, and when methodological nationalism occludes PLSTs.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.033
GPT teacher head0.349
Teacher spread0.315 · 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