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Record W7133043607

“Indigenizing Settlement”: Investigating the Possibilities and Limitations of Indigenous-Immigrant Solidarity Through Immigrant Settlement Organizations

2023· dissertation· W7133043607 on OpenAlexaboutno aff
Yukiko Tanaka

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousImmigrationSolidaritySettlement (finance)RacismColonialismRefugeeFace (sociological concept)
DOInot available

Abstract

fetched live from OpenAlex

This dissertation investigates the possibilities and limitations of solidarity between immigrant and Indigenous communities when mediated through the immigrant settlement sector. I conducted participant observation, interviews, and sharing circles in a program I call the Indigenous-Newcomer Training Program (INTP), which brings together Indigenous and immigrant youth in employment seeking, along with interviews and document analysis in the broader immigrant serving sector in Saskatoon, SK, Canada. In my first empirical chapter, I find that contrary to previous literature on immigrant-Indigenous relations, the sector is deeply invested in acknowledging the First Peoples of the land and resisting anti-Indigenous racism among immigrants. While these organizations are taking steps toward building relationships with Indigenous communities, they also face limitations in terms of funding, overburdening Indigenous colleagues, and maintaining Western ways of knowing. My second empirical chapter investigates the ways INTP’s employment programming demonstrates alternatives to neoliberalism and settler colonialism by drawing on Indigenous ways of knowing. I argue that INTP resists the neoliberal self-reliance that other state-funded programs attempt to inculcate in immigrant and Indigenous job seekers by focusing on healing at individual and community levels instead of individual skill development. Yet, because of the constraints presented by INTP’s reliance on state funding, the extent to which they can resist is limited. In my final empirical chapter, I turn to the ways Indigenous and immigrant youth come to (re-)interpret each other through the frames provided by INTP. I find that when immigrants compare settler colonialism in Canada to the colonialisms their home countries went through, rather than building solidarity, these comparisons reveal resentment of Indigenous people. I argue that rather than using colonial comparison to absolve themselves of settler complicity, immigrants make these comparisons to become settlers themselves. Overall, this dissertation argues for analysis in migration studies that keeps settler colonialism in view and takes Indigenous solidarity as an imperative. By conceptualizing the empirical case of INTP as an opportunity to reconstruct theory on settlement agencies and immigrant-Indigenous relations, my study brings the literature up to speed with this reality on the ground, and offers an empirical case study in a largely theoretical field.

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)0.016
metaresearch head score (Gemma)0.015
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 score0.979
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0250.035
Scholarly communication0.0130.010
Open science0.0030.020
Research integrity0.0030.004
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 head0.046
GPT teacher head0.350
Teacher spread0.304 · 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
Published2023
Admission routes1
Has abstractyes

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