Strategic Migrant Network Building and Information Sharing: Understanding ‘Migrant Pioneers’ in Canada
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.
Bibliographic record
Abstract
Abstract This article explores the migrant networks that develop between migrants, non‐migrants and the larger Indian diaspora. Specifically, it examines the decision to migrate to Toronto, Canada and how this decision is shaped by, and in turn shapes the migrant network. Based on 35 interviews with migrants from Karnataka, South India, two main findings are presented. First, migrants are deliberately choosing settlement countries in which their families are not yet located, thereby becoming “migrant pioneers” in their country of settlement, which is an attempt to expand their migrant networks globally. Second, the narratives these migrants receive and subsequently impart to others are often inaccurate, which can lead to miscommunication flows among these migrant networks. These findings are considered in light of the large body of research on migrant networks and the ways they develop and transmit information. This paper argues that existing understanding of migrant networks is somewhat static. Findings indicate that these “migrant pioneers” may be engaging in global risk‐diversification strategies for subsequent generations, but may themselves suffer from the more immediate consequences of misinformed networks.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it