MétaCan
Menu
← Back to cohort
Record W7052376616

Remittance Practices of Iranian Immigrants in Canada: A Mixed-Methods Study

2025· dissertation· en· W7052376616 on OpenAlexaffabout

Bibliographic record

VenueMacSphere (McMaster University) · 2025
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRemittanceImmigrationSanctionsState (computer science)Perspective (graphical)Economic sanctions
DOInot available

Abstract

fetched live from OpenAlex

This dissertation explores the remittance practices of Iranian immigrants in Canada, focusing on why and how they continue to send remittances to Iran despite structural challenges, particularly economic sanctions and the absence of formal remittance channels. Using a mixed-methods approach, it provides the first comprehensive investigation into the remittance behaviour of this understudied group, both within Canadian and global migration research. In doing so, it fills a significant gap in the literature by offering a sociological perspective on the intersection of state economic sanctions and individual remittance behaviour. By distinguishing between family remittances and migrant philanthropy, this dissertation offers a nuanced understanding of immigrant remittance practices, emphasizing the distinct emotional and moral dimensions that shape each type of remittance. This distinction challenges the prevailing literature, which often treats remittance behaviour as a homogeneous phenomenon. Chapter 3 uses large-scale data to provide a statistical overview of Iranian immigrants' remittance practices, comparing them to those of other migrant groups. It highlights Iranian immigrants' unique remittance patterns, shaped by sociodemographic factors and macro-level constraints such as economic sanctions. The chapter reveals that Iranian immigrants in Canada are more likely to send money to countries other than Iran than to Iran, and when remittances are sent to Iran, the amounts tend to be lower than the amounts sent elsewhere. This finding underscores the impact of structural constraints on the remittance behaviour of this group. Chapter 4 focuses on family remittances, analyzing the decisions behind them and the socio-cultural and micro-level determinants that influence these practices within the broader structural constraints. This chapter examines challenges with remittance methods, and the moral and emotional motivations for providing financial support. It reveals that while remittances often begin as voluntary acts, they are deeply rooted in an internalized moral obligation. Over time, these practices can lead to expectations from families/relatives left behind and, ultimately, migrants associate them with negative emotions such as anxiety, stress, and feelings of betrayal. Chapter 5 examines migrant philanthropy, exploring the primary concerns and motivations behind it, including how remitters select philanthropic causes, determine remittance patterns, and navigate emotional factors. It finds that the moral framework guiding these practices is often detached from the recipients' immediate needs, allowing for greater flexibility and relief for the remitter. While migrant philanthropy is generally associated with positive emotions such as reward, pride, and fulfillment, the experience is not always straightforward. Guilt plays a significant role in shaping this emotional experience, complicating the otherwise positive feelings that might arise from engaging in philanthropic acts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0090.002
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.286
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Explore more

Same venueMacSphere (McMaster University)→Same topicMagnetic confinement fusion research→French-language works237,207→