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Record W7133055456

“The Journey of Relocation,” A Reflective Autoethnography, Digital Story Telling, and Netnography: Experiences of South Asian Immigrants in Canada

2025· dissertation· W7133055456 on OpenAlexaboutno aff
SARAH ALAM

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaImmigrationSubalternNarrativeTransnationalismAutoethnographyMulticulturalismEthnographyColonialism
DOInot available

Abstract

fetched live from OpenAlex

Abstract by: Sarah AlamThis study, “The Journey of Relocation,” A Reflective Autoethnography, Digital Storytelling, and Netnography: Experiences of South Asian Immigrants in Canada, explores the multifaceted narratives of South Asian migrants navigating cultural, social, and systemic landscapes in Canada. By employing a hybrid qualitative methodology, the study integrates three distinct yet complementary approaches: reflective autoethnography to examine the researcher’s personal migration journey, digital storytelling to amplify migrant voices through multimedia narratives, and netnography to analyze online communities where South Asian diasporas negotiate identity, belonging, and resistance. This study investigates the complex realities of South Asian migrants in Canada amid rising anti-immigration sentiments post-COVID-19 and systemic inequities rooted in colonial legacies and shifting immigration policies. By combining reflective autoethnography, digital storytelling, and netnography, the study bridges personal, communal, and digital narratives to explore how South Asian individuals navigate cultural belonging, systemic marginalization, and the formation of intersectional identities in a sociopolitical climate increasingly hostile to racialized migrants. The research foregrounds the lived experiences of the researcher to reveal how displacement, acculturation, and labor inequities intersect with resilience strategies such as cultural preservation, digital activism, and transnational kinship. It critiques Canada’s multiculturalism as a contested ideal, exposing disparities between institutional rhetoric and migrants’ encounters with racism, bureaucratic exclusion, and media-driven homogenization of “visible minorities.” By contextualizing present-day struggles within historical frameworks, including colonial histories, post-independence South Asian geopolitics, and Canada’s exclusionary immigration past, the study highlights how intergenerational trauma and the duality of “home” shape migrant agency. Challenging gaps in diaspora scholarship, this work prioritizes subaltern voices through migrant-centered methodologies, interrogating how anti-immigration discourses disproportionately impact South Asians economically, socially, and culturally. It also examines digital spaces as sites of resistance and solidarity, where diasporas reclaim narratives erased by mainstream media. Beyond academia, this thesis aims to empower prospective South Asian migrants with critical insights into systemic barriers while advocating for policy reforms that address intersectional inequities. Ultimately, it reimagines migration as a nonlinear, contested journey of adaptation, a dynamic interplay of loss, survival, and reclamation in the pursuit of belonging. Keywords: South Asian migrants, Diaspora studies, Anti-immigration sentiments, Systemic marginalization, Intersectional identity, Cultural preservation, Colonial legacies, imperialism, capitalism, decolonial lens,

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0370.020
Scholarly communication0.0070.003
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.331
Teacher spread0.311 · 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 routes1
Has abstractyes

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