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Record W149259806

Analyse spatiale de la conflictualité, exploration par la régression géographiquement pondérée

2013· article· fr· W149259806 on OpenAlexaboutno aff
Elisabeth Salazar, Florent Joerin, Mathieu Pelletier, Stéphane Joost, François Golay

Bibliographic record

VenueInfoscience (Ecole Polytechnique Fédérale de Lausanne) · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt
DOInot available

Abstract

fetched live from OpenAlex

Cette recherche porte sur l’analyse spatiale de 1600 conflits urbains s’étant produits entre 1965 et 2000 dans le territoire correspondant aux limites actuelles de la ville de Québec. L’article propose de renouveler l’analyse de la relation entre la fréquence spatiale des conflits et certaines variables socioenvironnementales urbaines. Tout d’abord, les conflits sont classés en utilisant un indice original mesurant leur niveau de conflictualité. Ensuite, l’analyse est réalisée à l’aide d’une régression géographiquement pondérée. Les résultats démontrent qu’au niveau globale et/ou local la régression géographiquement pondérée produit de meilleurs résultats que la régression linéaire ordinaire. Par ailleurs, on observe aussi que les variables socioenvironnementales explicatives varient, partiellement selon le niveau de conflictualité des conflits analysés. On note enfin que ces variables n’exercent qu’une influence partielle sur la distribution spatiale de l’activité conflictuelle. Autrement dit, dans certains secteurs urbains, l’activité conflictuelle est associée à d’autres facteurs que ceux mesurés dans cette étude.

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)0.003
metaresearch head score (Gemma)0.001
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
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.005
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.295
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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