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Record W4225535815 · doi:10.5281/zenodo.5725862

Local Financial Arrangements in Canada: An Introduction

2021· report· en· W4225535815 on OpenAlexaffabout
Martin Horák, Brittany VanDenBrink

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typereport
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsWestern University
FundersHorizon 2020 Framework Programme
KeywordsFinancial systemBusinessFinanceEconomics

Abstract

fetched live from OpenAlex

This entry has been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay”. LoGov aims to provide solutions for local governments that address the fundamental challenges resulting from urbanisation. To address this complex issue, 18 partners from 17 countries and six continents share their expertise and knowledge in the realms of public law, political science, and public administration. LoGov identifies, evaluates, compares, and shares innovative practices that cope with the impact of changing urban-rural relations in five major local government areas: (1) local responsibilities and public services, (2) local financial arrangements, (3) structure of local government, (4) intergovernmental relations of local governments, and (5) people’s participation in local decision-making. The present entry addresses local financial arrangements in Canada. The entry forms part of the LoGov Report on Canada. To access the full version of the report on Canada, other practices regarding local financial arrangements and to receive more information about the project, please visit: https://www.logov-rise.eu/. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.001

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 head0.068
GPT teacher head0.299
Teacher spread0.231 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes2
Has abstractyes

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