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Record W2784889655 · doi:10.3390/su10010108

Transforming Municipal Services to Transform Cities: Understanding the Role and Influence of the Private Sector

2018· article· en· W2784889655 on OpenAlexaff
Sara Hughes, Jacqueline Peterson

Bibliographic record

VenueSustainability · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSustainabilityPrivate sectorBusinessService delivery frameworkContext (archaeology)Public sectorAccountabilityPoliticsService (business)Public administrationEnvironmental planningEconomic growthMarketingEconomicsPolitical scienceEconomy

Abstract

fetched live from OpenAlex

Municipal services—such as water, energy, and waste management—play a significant role in shaping the sustainability of cities. In many places, these services are also fully or partially delivered by the private sector, but we are only beginning to understand the implications this has for the politics and administration of urban sustainability initiatives. In this paper, we use the case of organics waste recycling in the Twin Cities, Minnesota to identify and discuss three ways private sector engagement can shift the political and administrative landscapes of municipal service delivery: through the presence and form of accountability mechanisms, norms and conditions for entrepreneurship, and the feasibility and appropriateness of traditional policy tools for achieving urban sustainability transformations. The analysis highlights the need to better understand best practices available to local governments for pursuing urban sustainability in the context of privatization, the importance of public sector capacity, and the potential for corporate social responsibility in municipal service delivery.

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)0.000
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 score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.355
Teacher spread0.324 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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