MétaCan
Menu
Back to cohort
Record W2329013570 · doi:10.4000/belgeo.6229

Scale and the workplace as level of analysis in transport geography

2012· article· en· W2329013570 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.

Bibliographic record

VenueBELGEO · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsTransport Canada
Fundersnot available
KeywordsVariance (accounting)Scale (ratio)Exploratory analysisMode of transportPoint (geometry)Mode (computer interface)Intervention (counseling)Time geographyRegional scienceEconomic geographyHuman geographyGeographySociologyPsychologyHistorical geographyComputer scienceTransport engineeringEngineeringData scienceEconomicsMathematicsCartographyDevelopment geographyPublic transport

Abstract

fetched live from OpenAlex

It is often stated that one of the advantages of geography is its ability to include various spatial scales (other than the individual). In transport policy, the workplace is increasingly seen as a level of intervention which, as a consequence, should be researched by geographers. The present essay discusses the workplace as level of analysis in transport geography. Exploratory measures indicate that 12 to 65 % of the variance in mode choice can be attributed to this level, with considerable differences between modes. However, these measures ignore the relationships and interactions of and between employees. An alternative, network-based view on workplaces is illustrated by means of a small case study. The empirical examples are the starting point for a discussion of some methodological issues related to analyses at multiple levels.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.034
GPT teacher head0.304
Teacher spread0.270 · 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