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Record W4237827033 · doi:10.32920/ryerson.14649762.v1

Constructed identities and appropriated spaces : an exploratory study of South Asian identity and space in Toronto

2021· preprint· en· W4237827033 on OpenAlexaffabout
Anne Katherine Herteis

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIdentity (music)Situational ethicsEthnic groupSpace (punctuation)Gender studiesExploratory researchHybridityGeographySociologySouth asiaEthnologyAnthropologySocial psychologyPsychology

Abstract

fetched live from OpenAlex

"South Asian" is a term commonly used in Canada to refer to individuals with ancestry in the Indian subcontinent and surrounding countries. The label has been created through Canada's means of statistical data collection on visible minority populations. Drawing from sociological, cultural studies, and geographic literature, this exploratory study seeks to determine the reciprocal relationship between South Asian identities as they are considered in Canada and urban space in Toronto. The research has been conducted through a critical review of literature regarding ethnic identity, hybridity, the production of urban space, and two key informant interviews. The key findings of the research suggest that South Asian identities are often multiple/situational, and that certain aesthetic aspects of South Asian identity are displayed in urban spaces in Toronto which may be labelled South Asian. These spaces may be considered hybrid spaces.

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)0.003
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 score0.127
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0250.012
Scholarly communication0.0050.002
Open science0.0020.008
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 head0.040
GPT teacher head0.313
Teacher spread0.274 · 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
Published2021
Admission routes2
Has abstractyes

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