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Record W7155494749 · doi:10.1353/ces.2025.a989104

Trustcraft and Trustweb: Navigating Information and Emotion by Highly Skilled Migrants in Canada

2025· article· en· W7155494749 on OpenAlexvenueaboutno aff
Ashika Niraula

Bibliographic record

VenueCanadian ethnic studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationImmigrationSettlement (finance)Vulnerability (computing)Work (physics)DyadFace (sociological concept)

Abstract

fetched live from OpenAlex

Abstract: Migrants, including those with higher education credentials, face challenges while navigating immigration policies and labour market in host countries, including Canada. During the migration and settlement process, accessing credible information is essential to maintain migrants’ sense of control and direction. Drawing on 18 semi-structured interviews (2022–2023) with highly skilled migrants (HSMs) on varied temporary work permits in Canada, this article examines how they navigate information through trustcraft (i.e., the strategic, emotional work of deciding which information and what source to believe) and the formation of trustweb (i.e., a dynamic network of varied information sources, or trust points, that assemble over time). Importantly, these two processes are relational and mutually constitutive. What makes the trustcraft-trustweb dyad unique is not only its content but the ongoing negotiation of (dis)trust across information sources. The information searching process is inherently uneven and shaped by HSMs’ geopolitical background and access to resources (e.g., financial means), which in turn shape one’s vulnerability to risk and emotional strain. Hence, migration information seeking should be understood as a stratified, relational practice rather than a neutral, purely cognitive task. Résumé: Les migrants, y compris ceux diplômés de l’enseignement supérieur, rencontrent des difficultés pour naviguer dans les politiques d’immigration et le marché du travail en pays d’accueil, le Canada inclus. Au cours du processus de migration et d’intégration, l’accès à des informations fiables est essentiel pour permettre aux migrants de maintenir un sentiment de contrôle et éviter de se sentir désorientés. Cet article s’appuie sur 18 entretiens semi-directifs (2022–2023) menés avec des migrants hautement qualifiés (MHQ) et titulaires de différents types de permis de travail canadiens. L’article analyse la manière dont les migrants surfent sur l’information à travers le trustcraft (c’est-à-dire le travail stratégique et émotionnel consistant à décider quelles informations et quelles sources croire) et à travers la formation d’un trustweb (c’est-à-dire un réseau dynamique de différentes sources d’information, ou de points de confiance, qui se constitue au fil du temps). Ces deux processus sont relationnels et mutuellement constitutifs. Le système trustcraft–trustweb est unique non seulement par son contenu, mais aussi par la négociation continue de la défiance (ou de la confiance) entre les différentes sources d’information. Le processus de recherche d’information est intrinsèquement inégal, et est façonné par le parcours géopolitique des MHQ et par leur accès à diverses ressources (par exemple, financières), lesquels influencent leur vulnérabilité au risque et à l’épuisement émotionnel. Ainsi, la recherche d’information en contexte migratoire doit être comprise comme une pratique stratifiée et relationnelle, et non comme un travail neutre et purement cognitif.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.423

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 communication0.0000.001
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 head0.032
GPT teacher head0.330
Teacher spread0.297 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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 routes2
Has abstractyes

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