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Record W4220981289 · doi:10.1145/3490555

A Decade of International Migration Research in HCI: Overview, Challenges, Ethics, Impact, and Future Directions

2022· article· en· W4220981289 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.

Bibliographic record

VenueACM Transactions on Computer-Human Interaction · 2022
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoliticsSociologyDomain (mathematical analysis)Engineering ethicsFocus (optics)Political science

Abstract

fetched live from OpenAlex

This article presents a thorough discussion of the trajectories of international migration research in HCI. We begin by reporting our survey findings of 282 HCI-related publications about migration from nine digital libraries between 2010–2019, summarizing how this research stream has evolved, the geographies and populations it encompasses, and the methodologies it utilizes. We then augment these findings with data from interviews with 11 skilled researchers who reflect on their working experience in this area. Our analysis reveals how the domain has evolved from the European migrant crisis to a more global agenda of migration and points towards a shifting focus from addressing immediate needs to acknowledging more complex political and emotional aspects of mobility. We also uncover the critical role of academic, local, and international politics in migration research in HCI. We discuss these findings to explore future opportunities in this area and advance HCI research discourse with the marginalized populace.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.145
GPT teacher head0.427
Teacher spread0.282 · 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