Bibliographic record
Abstract
GIS eased into geography without much discord until the 1990s, when a flurry of commentaries about the relative merits of GIS made their way into a number of geographic journals. The ensuing decade was marked by varying degrees of friction between GIS practitioners and their critics in human geography. Despite the methodological chasm between the two groups, little discussion of the implications of these differences has ensued. This article fills that gap with a historiographic examination of critiques of GIS. Critiques of GIS are organized into three waves or periods, each characterized by distinct arguments. The first wave, from 1990 to 1994, was marked by the intensity of debate as well as an emphasis on positivism. By 1995, the conversation waned as the number of critics grew, while GIS practitioners increasingly declined comment. This second wave marked the initiation of a greater degree of co-operation between GIS scholars and their critics, however. With the inception of the National Center for Geographic Information Analysis (NCGIA) Initiative 19, intended to study the social effects of GIS, many critics began to work closely with their peers in GIS. In the third wave, critiques of GIS expressed a greater commitment to the technology. Throughout the decade, debates about the technology shifted from simple attacks on positivism to incorporating more subtle analyses of the effects of the technology. These critiques have had considerable effect on the academic GIS community but are presently constrained by limited communication with GIS practitioners because of the absence of a common vocabulary. I argue that, if critiques of GIS are to be effective, they must find a way to address GIS researchers, using the language and conceptual framework of the discipline.
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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 | 0.035 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.020 | 0.072 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.019 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".