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Record W4200137729 · doi:10.3390/socsci10120485

Unpacking the Role of Neoliberalism on the Politics of Poverty Reduction Policies in Ontario, Canada: A Descriptive Case Study and Critical Analysis

2021· article· en· W4200137729 on OpenAlexafffundabout
Jessica K. Gill

Bibliographic record

VenueSocial Sciences · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Waterloo
FundersYork University
KeywordsNeoliberalism (international relations)GrassrootsPoliticsPovertyIdeologySociologyPolitical economyCulture of povertyPower (physics)Political scienceCritical theoryEconomic growthDevelopment economicsEconomicsBasic needsLaw

Abstract

fetched live from OpenAlex

This paper employs a descriptive case study method to analyze and critically review the emergence of the provincial poverty reduction strategy in Ontario, Canada which was implemented in 2008 and renewed in 2014. The purpose of this study is two-fold: first, it defines the principles of neoliberalism and explores the historical growth of neoliberal thought in Canada, and specifically within Ontario, beginning in the 1980s to the present-day. Drawing on a combination of primary, secondary and grey literature, this paper discusses the ways in which neoliberal ideologies and rhetoric became deeply rooted in political thought and discourse within the province. Employing a critical theory framework, the paper highlights the contrasting ways in which neoliberal values were adopted by the different political parties in power and the detrimental impact this espousal had on individuals living in poverty within Ontario. Second, the paper illustrates the powerful ways in which anti-poverty grassroots movements and social advocacy groups assembled to push for the creation of a provincial poverty reduction strategy. The analysis ends with a critique of the neoliberal influences on the strategy’s recommendations and the future outlook of the poverty reduction strategy based on the current political climate within the province.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.263
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations13
Published2021
Admission routes3
Has abstractyes

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