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Record W4297769381 · doi:10.5267/j.dsl.2022.5.005

Determining the urban economic resilience planning through ratio of original local government revenue

2022· article· en· W4297769381 on OpenAlex
Titi Purwandari, Sukono Sukono, Yuyun Hidayat, Wan Muhamad Amir W Ahmad

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.

venuePublished in a venue whose home country is Canada.
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

VenueDecision Science Letters · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsnot available
FundersUniversitas Padjadjaran
KeywordsResilience (materials science)Index (typography)Variable (mathematics)RevenueEconomicsVariablesGovernment (linguistics)Regression analysisEconometricsDisturbance (geology)StatisticsMathematicsComputer science

Abstract

fetched live from OpenAlex

Today, the economic resilience in Indonesia measures using the index approach, but it does not consider the effect of the disturbance and causes meaningless. The index is essentially an average, and the average is not a model that captures the relationship between variables. This research differs significantly from earlier studies that used the index to measure economic resilience. The crucial step in assessing the economic resilience of a city is to determine the economic resilience decision variable itself. If a variable significantly correlates with the disturbance factors in each relationship pattern, it is considered suitable as an economic resilience variable. This study evaluates variable Z as an economic resilience variable with a significant relationship to its disturbance variable. The evaluation method is conducted in-depth by studying Indonesia's cities over five years (2015-2019). Z, the ratio of Original Local Government Revenue (PAD) to the number of poor people in a city as a cost centre, will be evaluated as a prospective decision variable for economic resilience. The statistical relationship between Z and 9 disturbance variables is examined using piecewise linear regression analysis. All 514 cities in Indonesia were observed extensively for identification during a five-year observation period. Rosenbrock pattern search estimation was used to estimate the model parameters. The following results were obtained by analysing the data with the STATISTICA software. As determined by parsimonious analysis, the price of Pertalite fuel and the US dollar foreign exchange are two disturbance factors that are crucial to the fall in the resilience variable Z. The joint effect of these two variables on the decline in the resilience measure Z is 73.63 percent. The study concludes that Z is a city-level economic resilience decision variable that applies to all 514 cities in Indonesia and is measured as the ratio of PAD to the number of poor people. This study's novel contribution to Indonesian policymakers is Z as a new economic resilience decision variable that can be used to assess cities' relative economic resilience.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.540

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 science0.0010.000
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 head0.037
GPT teacher head0.275
Teacher spread0.238 · 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