MétaCan
Menu
Back to cohort
Record W2072764623 · doi:10.1177/0275074012451523

Developing a Method to Assessing the Municipal Financial Health

2012· article· en· W2072764623 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe American Review of Public Administration · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsWeightingMultivariate statisticsPrincipal component analysisVulnerability (computing)Actuarial scienceFlexibility (engineering)PopulationSocioeconomic statusMultivariate analysisConceptual frameworkBusinessEconometricsAccountingComputer scienceEconomicsStatisticsEnvironmental healthMedicineMathematicsSociology

Abstract

fetched live from OpenAlex

Following the conceptual framework developed by the Canadian Institute of Chartered Accountants, which is based on three broad dimensions of sustainability, flexibility and vulnerability, this paper proposes a method for evaluating the financial health of municipalities. This methodology could be useful for performance assessment in any country and framework. An aggregate indicator has been obtained for each municipality that covers all the aspects analyzed. For this, multivariate statistical techniques of principal component analysis and discriminant analysis are combined. The proposed method overcomes the problem that we detected in the literature related to the weighting of variables, optimizing the measurement of the variability of all indicators that are included in the financial condition. The indicator evaluates and ranks the degree of financial health of each municipality and serves as a tool to study how different factors might have an impact on its financial health. The performance of the indicator has been contrasted with the socioeconomic variables of population size and geographic location. The proposed method has been applied to 5,165 Spanish municipalities.

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)0.005
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.902
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.145
GPT teacher head0.400
Teacher spread0.255 · 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