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Record W2531669331

"It was easy to look for a place, but hard to actually get one": University students' experiences of racial discrimination in off-campus housing

2016· dissertation· en· W2531669331 on OpenAlexaboutno aff
Cara Nightingale

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationSociologyPsychologyPedagogy
DOInot available

Abstract

fetched live from OpenAlex

This study examines university student perceptions of and experiences with racial discrimination in off-campus housing in Ontario’s Niagara Region. Using a qualitative methodology informed by critical race theory, the study draws upon semi-structured, qualitative interviews conducted with 14 Brock University students to gain insight into racial discrimination in the context of the search for and life in off-campus housing. Participants discussed the wider context of off-campus housing in the region, including certain difficulties related to student inexperience in the off-campus housing market, age, and gender. Along with uncovering these other challenges faced by students, the thesis documents and analyses accounts of the impact of racialized identities and racism at different stages of the student off-campus housing search and subsequent residency. By documenting and analyzing these perceptions and experiences, this study seeks to contribute to wider efforts to expose and challenge racial discrimination.

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 score0.876
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0180.010
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0010.003
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 head0.018
GPT teacher head0.252
Teacher spread0.235 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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