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Recuperación de plusvalías para el desarrollo urbano: una comparación inter-americana

2003· article· es· W2046087894 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEURE (Santiago) · 2003
Typearticle
Languagees
FieldSocial Sciences
TopicLatin American Urban Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Local governments design a broad range of fiscal or regulatory policies that have been inspired by the idea that land value increment may be mobilized to the benefit of the community -that is of land value capture. This paper compares the experiences of North America (US and Canada) and Latin America with value capture tools and discusses the reasons why different policies have been favored and different results and degrees of success obtained in their implementation. Focusing on broad categories of value capture policies, the first part of the paper compares the overall performance and/or experience of the two regions with the capturing of land value increment through conventional taxes, fees and regulatory urban policy instruments. The second part of the paper shows that the same "value capture principle" to address similar problems (to deepen land value taxation; to finance urban infrastructure; to control land use) result in different outcomes (sometimes even opposite) in different contexts, most notably those presented in North America and Latin America, respectively. The paper's concluding section provides some evaluative comments regarding the apparent lag between the intentions and outcomes of value capture policies as experienced by the two regions.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.354
Teacher spread0.323 · 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