A hard binary to shake: The limitations and possibilities of teaching GIS critically
Bibliographic record
Abstract
This paper builds upon studies employing a syllabi‐based methodology that suggest a tendency for critical geographic information science (GIS) courses to emphasize reading/discussion about GIS without actually doing GIS, and for traditional GIS instruction courses to emphasize the technical capacities of GIS software without incorporating critical theory in substantive ways. However, through ethnographic evidence we reveal that there is likely more innovative theory‐practice transcending pedagogies being utilized than would necessarily show up in such a syllabi‐based methodology. There are also very real and differentially manifest pragmatic, departmental, and institutional barriers in place to effectively incorporating critical social theory into courses that actually do GIS. We first catalogue these barriers as a means of ascertaining what can (and cannot) be done to overcome them through GIS pedagogic innovation. We then outline the (often‐veiled) pedagogic strategies deployed by critical GIS scholars today to navigate and circumvent these barriers.
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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 | 0.043 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.048 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".