MétaCan
Menu
Back to cohort
Record W2127424603

GIS for the public sectorc Experiences from the city of Belo Horizonte, Brazil

2000· article· en· W2127424603 on OpenAlexaff
Karla Albuquerque de V. Borges, Sundeep Sahay

Bibliographic record

VenueInformation Polity archive · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeographic information systemSanitationPublic participation GISEnvironmental planningSituatedGIS DayGovernment (linguistics)Local governmentGeographyGIS and public healthEnvironmental resource managementEnvironmental protectionCartographyComputer scienceEngineeringEnvironmental engineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Belo Horizonte was one of the first Brazilian municipal administrations to develop an urban Geographic Information System. Situated within the local government tradition of local government, the development and implementation of the Geographic Information System (GIS) commenced in 1989 and has proceeded significantly to the extent that it has become the most complete experience of its kind throughout Brazil, with applications covering areas such as education, health, sanitation, urban planning, transportation and traffic, among others. This article reflects on the experiences of this GIS project, from the technology acquisition and team formation phases, through the creation of the geographic database, to the development of applications and dissemination among users. Current perspectives for the continuing expansion of GIS technology usage in Belo Horizonte are also presented. This “successful” experience of GIS implementation is contrasted with some GIS projects in India to highlight probable areas of emphasis in future GIS projects in developing countries.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.002
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 head0.028
GPT teacher head0.291
Teacher spread0.264 · 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 designQualitative
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

Citations5
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueInformation Polity archiveSame topicGeographic Information Systems StudiesFrench-language works237,207