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Record W2102616252 · doi:10.1177/0042098013489742

Understanding the Impact of the Modifiable Areal Unit Problem on the Relationship between Active Travel and the Built Environment

2013· article· en· W2102616252 on OpenAlex
Andrew Clark, Darren M. Scott

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUrban Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)GeographyBuilt environmentMeasure (data warehouse)StatisticsCartographyComputer scienceMathematicsEngineeringData miningCivil engineering

Abstract

fetched live from OpenAlex

This study examines how the relationship between active travel (AT) and the built environment is influenced by the modifiable areal unit problem (MAUP). Characteristics of the built environment are measured at 14 geographical scales. At each scale, these characteristics are related to a binary measure of AT using a logit model. The data for this study come from the Space–Time Activity Research (STAR) project, which was conducted in Halifax, Canada, between April 2007 and May 2008. The variable coefficients and their significance are examined for MAUP influences. The results suggest that the relationship between AT and the built environment is indeed impacted by the MAUP. The results are used to suggest guidelines for selecting an appropriate scale at which to measure the built environment in order to minimise MAUP effects.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.280
GPT teacher head0.348
Teacher spread0.068 · 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