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Record W3190827159 · doi:10.7202/1078393ar

SAFE STREETS FOR REAL PEOPLE: A CASE STUDY OF NEOCONSERVATIVE POLICY FROM A STRUCTURAL SOCIAL WORK PERSPECTIVE

2021· article· en· W3190827159 on OpenAlexvenueaboutno aff
Élyse LeBlanc

Bibliographic record

VenueCanadian social work review · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologySociologyPunitive damagesPoliticsContext (archaeology)CriminologyBlameLaw and economicsPolitical economyPolitical scienceLawSocial psychologyPsychology

Abstract

fetched live from OpenAlex

The Safe Streets Act of Ontario [ SSA ] ostensibly regulates aggressive panhandling, but is widely regarded as a contemporary vagrancy law that criminalizes people experiencing homelessness. This paper presents a case study of the SSA in which an ideological analysis is employed to highlight the extent to which dominant political paradigms shape conceptions of social problems and their appropriate remedies. Specifically, it explores the mechanisms inherent to neoconservative ideology which serve to blame individuals for their problems and construct vulnerable people in need of support as villains worthy of exclusion and punishment, rationalizing punitive responses to poverty. This approach is diametrically opposed to the aims of structural social work and therefore must be challenged. An alternative policy response is presented as it might emerge from a social democratic worldview, which is more congruent with social work ideals. This paper thus illustrates how radically the nature of social problems is transformed when viewed through contrasting ideological lenses. The paper concludes that there is great value in using political paradigms to unpack existing and create new policy in the context of structural social work mandates; doing so contributes to the paradigm shift that a profession committed to fundamental social change must help ignite.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.003
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.088
GPT teacher head0.460
Teacher spread0.372 · 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.

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

Citations1
Published2021
Admission routes2
Has abstractyes

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