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Record W4412123403 · doi:10.32920/29521751.v1

The Digital Im/migrant: IS in Migration Governance, Work, and Life

2025· preprint· en· W4412123403 on OpenAlexfundno aff
Pedro Seguel, Mireille Paquet, Ashika Niraula, Mylène Coderre, Émile Baril, Stein Monteiro

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
FundersCanada First Research Excellence Fund
KeywordsWork (physics)Corporate governanceBusinessPolitical scienceSociologyEngineering

Abstract

fetched live from OpenAlex

<p dir="ltr">This panel explores how digital technologies shape the migration experience across governance, labor, and decision-making. While digital systems increasingly organize citizens’ lives, their role in shaping migrants’ experiences is less visible, especially for those navigating unfamiliar institutions and limited legal status. Drawing on empirical research, this panel examines tensions in how digital infrastructures affect migrant-state relations and platform-mediated labor markets. Panelists address topics such as the modernization of immigration institutions, social media use in migration planning, digital labor recruitment across the Americas, and algorithmic control in gig work. In dialogue with core IS concerns—sociotechnical systems, platform governance, and information-seeking behavior—the panel situates digital migration systems within broader political, structural, and ethical contexts. This interdisciplinary session fosters debate on tensions between technological innovation and equity. By tackling these issues, the panel invites IS scholars to see migration as a vital context for rethinking inclusion, infrastructure, and institutional transformation.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.012
GPT teacher head0.244
Teacher spread0.233 · 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.

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
Published2025
Admission routes1
Has abstractyes

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