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Record W2088015763 · doi:10.1080/00045608.2011.592727

You Don't Need Sight to Have Vision: Reginald G. Golledge Was a Giant in Analytical Human Geography

2011· article· en· W2088015763 on OpenAlexaboutno aff
Robert J. Stimson

Bibliographic record

VenueAnnals of the Association of American Geographers · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)ClubGovernment (linguistics)PublishingHistoryArt historyLawPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Click to increase image sizeClick to decrease image size Acknowledgments On the evening of 29 May 2009, Reginald George Golledge, above-scale Professor of Geography in the Geography Department at the University of California Santa Barbara, passed away at his home in Goleta after enduring a long series of illnesses. He was 71. Golledge was an intellectual giant in his field. Notes 1. That included fellow geographers Torsten Hagerstrand, Julian Wolpert, Peter Gould, and Roger Downs, and psychologist David Stea. 2. That included state governments and transportation planning agencies in the states of New South Wales, Victoria, and West Australia in Australia; the National Government of The Netherlands; and private firms in Japan, Canada, and the United States. 3. It was 1960 as a first-year student at UNE when I met Reg Golledge and was taught by him. He was the moral tutor in charge of a small group of male students living in the townhouse "Esrom" in Armidale. 4. He was the proud editor of the "University Rugby Club Song Book," which, he would nostalgically recall, was his cherished first and arguably most popular publication but one that a publishing house could not possibly print for fear of prosecution! 5. He was scheduled to give the public lecture later in the year, but death intervened.

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)0.002
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 score0.074
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.052
GPT teacher head0.367
Teacher spread0.315 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2011
Admission routes1
Has abstractyes

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