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Record W3111507216 · doi:10.17345/rcda2913

Business Improvement Districts y sostenibilidad urbana. A propósito de la regulación de las áreas de promoción de la actividad económica urbana en Cataluña

2020· article· en· W3111507216 on OpenAlexaboutno aff
Irene Araguàs Galcerà

Bibliographic record

VenueRevista Catalana de Dret Ambiental · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAdministrative Law and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCatalanPromotion (chess)DecentralizationLegislationGeneral partnershipWelfare economicsCONTESTRegulatory authorityOrder (exchange)BusinessPolitical scienceHumanitiesPublic administrationEconomicsFinanceMarket economyLaw

Abstract

fetched live from OpenAlex

This paper analyzes environmental problems caused by commercial activities in the dispersed city model, and the contribution of the Business Improvement Districts (BID) in this matter. A Business Improvement District is a public-private partnership in which business of a defined area decide to pay a levy in order to provide supplemental services to those provided by the municipality. BID’s action contributes to urban generation and helps to fight against decentralization. The first BID was established in Canada but nowadays there are so many European countries with BIDs, and it is expected that Spain will have a complete regulation of BIDs very soon. Catalan trade legislation has been the first to contemplate an equivalent figure –the Urban Economic Activity Promotion Areas- and, currently, the Parlament of Catalonia is currently considering a Bill.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0080.001
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.292
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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