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Record W2063386367 · doi:10.1177/0969776407077188

Observing Regularities in Location Patterns

2007· article· en· W2063386367 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

VenueEuropean Urban and Regional Studies · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsEconomic geographyMetropolitan areaEconomies of agglomerationCensusGeographyPopulationCrowdingRegional scienceDemographic economicsEconometricsDemographyEconomicsEconomic growthSociologyPsychology

Abstract

fetched live from OpenAlex

The location of economic activity in Spain is analysed, employing a methodology previously applied to Canada. We ask whether the regularities posited for Canada also hold for Spain, despite the differences in geography. Using census data for the years 1991 and 2001, Spain's 8,086 municipalities are classified according to population size and distance thresholds analogous to those applied to Canada.The location patterns of industries are plotted in relation to these classes. The results reveal, on the whole, spatial distributions consistent with posited regularities and previous findings. Location patterns are fairly stable over time, reconfirming the continued weight of distance and of agglomeration economies. The results also show a crowding-out process in Spain, similar to that observed for other nations, fuelling the growth of manufacturing activity in locations in close proximity to metropolitan areas.

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 score0.430
Threshold uncertainty score0.486

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 studies0.0000.000
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 head0.083
GPT teacher head0.234
Teacher spread0.151 · 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