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Record W7030415485

Navigating neoliberalism: context, discourse, and the social construction of street populations in Calgary and Montreal

2010· dissertation· en· W7030415485 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2010
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSocial constructionismGovernment (linguistics)PoliticsSocial justiceEconomic JusticeDiscourse analysisWelfare stateState (computer science)
DOInot available

Abstract

fetched live from OpenAlex

Citing a shift away from welfare provision in western societies, researchers have sought to understand how the governance of street populations has changed in the era of neoliberalism. Less state social support and a greater reliance on market mechanisms are often implicated in a more repressive, control-oriented response to problematized street populations. Examining newspapers, government documents, and police reports, the research explored the claimsmaking and typifications of street populations made by various social actors in Montreal and Calgary. Significant differences were found in the between the two cities. Language of inclusivity and justice were noted in Montreal, while the image of an out of control, decaying Calgary core was present. The research compared the social constructions made in each city, suggesting that differences in language and typifications are the result of wider cultural variables. Language of inclusivity and justice is tied to Quebec's unique social economy, while language of individuality and responsibility is tied to Albertan social and political economy.

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)0.005
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 score0.121
Threshold uncertainty score0.875

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0200.033
Scholarly communication0.0100.002
Open science0.0020.005
Research integrity0.0010.002
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 head0.027
GPT teacher head0.240
Teacher spread0.213 · 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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe Atrium (University of Guelph)→Same topicDiverse Scientific and Economic Studies→French-language works237,207→