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Record W7133035759

Neighbourhood Experiences as Reconciliation: Place, Blackness, and Moving Towards Right-Relations in Malvern,Toronto

2024· dissertation· W7133035759 on OpenAlexaboutno aff
Justin Rhoden

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)IndigenousCommissionImmigrationTreatyPosition (finance)Race (biology)
DOInot available

Abstract

fetched live from OpenAlex

The Truth and Reconciliation Commission Final Report (TRC) outlines that reconciliation is important for rebuilding the nation-to-nation treaty relations across Canada and all Canadians have an important role and responsibility in nurturing this new relationship. Despite the well-documented exclusion of Black peoples from all domains of Canadian society, research activism concerning reconciliation rarely attends to Canada’s (re)production of racialized hierarchies beyond a settler-native relationship positioning Blackness and the particular experiences of Black people as irrelevant or marginal in theorizing and realizing new geographies of relationality. This study contributes to our collective understanding of reconciliation by examining reconciliation at the axis of Blackness and neighborhood spaces. Towards these ends, I position Black residents’ everyday experiences with each other, their neighbours, the land, its Indigenous rights holders and their histories in Malvern, a racialize immigrant neighbourhood in east Toronto, as emblematic of the challenges and opportunities of supporting reconciliation across uneven geographies of race and racialization.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.056
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0450.019
Scholarly communication0.0060.002
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.349
Teacher spread0.336 · 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
Published2024
Admission routes1
Has abstractyes

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