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Record W7133031142

The Crescent Moon through Maple Trees: How Racializing Settlement Structures Reinforce Nonbelonging, and Perceptions of ‘Canadianness’ for Pakistani Newcomers

2025· dissertation· W7133031142 on OpenAlexaboutno aff
Hammad Khan

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)ImmigrationSymbolic capitalGovernmentalityRacializationIntersectionalityShadow (psychology)The SymbolicPerception
DOInot available

Abstract

fetched live from OpenAlex

In this dissertation, I develop nonbelonging as a sociologically relevant concept and heuristic by examining what it means to be “Canadian” for newcomers. Drawing on life-history interviews with newcomer Pakistani immigrants and first-generation settlement counselors, I show how nonbelonging is subtly reinforced during early settlement. First, I use Foucault’s concept of governmentality to analyze how the settlement service sector legitimizes nonbelonging at an institutional level. I demonstrate how institutional practices and social interactions reinforce nonbelonging, even in seemingly inclusive social institutions. Next, I apply Bourdieu’s theory of symbolic capital to examine how newcomers experience nonbelonging through the loss or devaluation of professional and educational credentials, linguistic fluency, and social status. These accounts reveal how structural and embodied forms of nonbelonging intersect. Finally, I use a postcolonial framework to show how whiteness continues to define authentic Canadianness. I analyze how Canada’s image as an “authentically” white nation reinforces racialized exclusion and structures perceptions of belonging (Mackey 1999; Thobani 2007), and how these perceptions coexist with nonbelonging. By centering the voices of Pakistani newcomers, this dissertation provides the first comprehensive study of how nonbelonging operates and is reinforced in latent ways for racialized immigrants in Canada. I argue that nonbelonging is not an unintended consequence of immigration but an active, structured, and ongoing condition that functions alongside racialized belonging. Across three studies, I demonstrate that institutions which appear inclusive, such as settlement service centers, often communicate messages of nonbelonging. Settlement counselors, who are themselves first-generation immigrants, draw on their own experiences of exclusion, normalizing these barriers for newcomers. For Pakistani immigrants, this process becomes embodied in the loss of symbolic capital and felt through contradictions between pre-migration expectations and post-migration realities. These interactions reflect and reproduce broader structures of whiteness that continue to define Canada’s national ethos. Ultimately, this dissertation shows how Canada’s immigration system simultaneously welcomes and excludes, producing a complex and contradictory experience for racialized newcomers like those from Pakistan. It makes visible the hidden processes of nonbelonging, challenging assumptions of inclusivity and calling for deeper sociological engagement with the intersections of race, migration, and belonging.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.459
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.014
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.374
Teacher spread0.353 · 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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