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Record W3199793979 · doi:10.1177/0160323x211038862

Municipal Takeovers: Examining State Discretion and Local Impacts in Michigan

2021· article· en· W3199793979 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueState and Local Government Review · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDiscretionBusinessBankruptcyFinanceContext (archaeology)RevenueFinancial distressState (computer science)Psychological interventionPublic economicsEconomicsFinancial systemPolitical science

Abstract

fetched live from OpenAlex

State interventions during municipal financial emergencies can play a critical role in ensuring the continuation of public services and preventing municipal bankruptcy but have often been applied unevenly. Using a case study of municipal takeovers in Michigan, we examine their predictability based on financial stress indicators and effects on drinking water services. We find financial stress alone does not explain takeover decisions, and that a city’s reliance on state revenue and racial and economic context play a role. Cities that have been taken over are more likely to experience drinking water privatization and rate increases than similarly financially stressed cities. The malleable definition of financial distress and discretion in implementation allow takeover policies to be applied unevenly, creating additional challenges for already distressed communities. Decision makers should seek alternative approaches to municipal financial emergencies that address underlying causes while minimizing the potential for bias and significant changes to public services.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.028
GPT teacher head0.230
Teacher spread0.202 · 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