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Record W4386108192 · doi:10.7764/onomazein.60.05

Jewish Toronto’: street naming policies and practices in the north of Metropolitan Toronto

2023· article· en· W4386108192 on OpenAlexaboutno aff
Yossi Katz, Liora Bigon

Bibliographic record

VenueOnomázein Revista de lingüística filología y traducción · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJudaismMulticulturalismMetropolitan areaEthnic groupJewish identitySociologyGovernment (linguistics)Media studiesPublic administrationGeographyEthnologyHistoryPolitical scienceLawAnthropologyArchaeology

Abstract

fetched live from OpenAlex

This article deals with street naming policies and practices with regard to the Jewish urban community in the north of Metropolitan Toronto, Canada. It highlights the linguistic landscape as a cultural and symbolic expression of a Jewish-Israeli minority group in Vaughan, a city in North Toronto. The Jewish nomenclature is also examined viewing Toronto’s multicultural- cum-pragmatic street naming policies. While such a display of Jewish toponymy is almost non-existent in Toronto itself, the creation of ‘Jewish Toronto’ in the north of the metropole is the product of both ‘Jewish’ and ‘Canadian-Torontonian’ factors. This article analyzes these two factors and their related characteristics in terms of demography, sociopolitical approach, religiocultural identity, economy, and municipal by-laws. It concludes that the development of a Jewish toponymic culture as an ethnic-minority culture in the public domain of northern Metropolitan Toronto is a result of a bipartite process. This process has been enabled by the aspirations of the minority group, on the one hand, and the flexibility and tolerance inherent in the multicultural policies of the majority group/ government, on the other.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.352
Teacher spread0.303 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueOnomázein Revista de lingüística filología y traducciónSame topicJewish and Middle Eastern StudiesFrench-language works237,207