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The Local Shape of Revolution: Reflections on Quantitative Geography at Cambridge in the 1950s and 1960s

2008· article· en· W2076264981 on OpenAlexfundno aff
Peter Haggett

Bibliographic record

VenueGeographical Analysis · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geography and Geographical Thought
Canadian institutionsnot available
FundersRoyal Geographical SocietyAustralian Research CouncilRoyal SocietyWilfrid Laurier University
KeywordsTheme (computing)Economic geographyHuman geographySociologyGeographyHistory

Abstract

fetched live from OpenAlex

The “quantitative revolution” in human geography which swept across so many universities in the 1950s and 1960s had its main diffusion centers in a few locations which were to have global significance. Two critical early centers were the University of Washington in the Pacific Northwest and Lund University in southern Sweden. But the experience of change was different in different locations as the general forces of perturbation sweeping around academia were translated into local eddies with local repercussions. Here, small and somewhat random quirks at the outset, led eventually to fundamental divergences between adoption and rejection. The theme is illustrated by reference to changes which occurred at Cambridge, one of England's two oldest universities, as seen from the perspective of someone who—as undergraduate, graduate student, and later, faculty member—was caught up in these changes and took some small part in propagating them. Special attention is given to the role of two environmental scientists, Vaughan Lewis and Richard Chorley, in introducing changes and the way in which later developments in human geography drew on preceding experiences in physical geography. The reasons behind the “Cambridge variant” and the questions of how intellectual DNA is passed across the generations are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.437

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0110.080
Scholarly communication0.0130.013
Open science0.0010.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.319
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations24
Published2008
Admission routes1
Has abstractyes

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