Placing ideas: genius loci, heterotopia and geography's quantitative revolution
Bibliographic record
Abstract
The paper is concerned with understanding the geography of intellectual creativity and change using as a case study the quantitative revolution in geography. First, I review briefly the sea change occurring over the last 40 years in understanding intellectual production, and made most forcefully in the literature in the sociology of scientific knowledge. I highlight three elements: the nature and persistence of intellectual breaks and ruptures; the embodiedness and material embeddedness of the intellectual process; and the centrality of networks and alliances. Secondly, I take each of these three components of intellectual production, and work them through different theories of place to illuminate the role of the geographical within each. In particular, I argue that the geography of intellectual rupture is clarified by using Michel Foucault's notion of heterotopia, that the place of intellectual embodiment and embeddedness is elucidated by Kevin Hetherington and John Law's work on materiality, and that spaces of network and alliance are enhanced by the recent writings on place by Nigel Thrift. Finally, using these three features I present an interpretive analysis of the place of geography's quantitative revolution drawing upon 36 oral histories I conducted with firstand second-generation pioneers of that movement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.072 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".