Lines Underground: Exploring and Mapping Venezuela's Cave Environment
Bibliographic record
Abstract
How do the lines on a map come into being? What stories do they tell? These questions are examined in the context of cave exploration and mapping in Venezuela. Ethnographic analysis focuses on mapping in the field, the translation of notes into final maps, and discourses surrounding these practices. The lines that cave surveyors sketch in field books while traversing underground passages reveal a dialectic between cartographic and exploratory practices. Two key factors shape this dynamic: first, the experience of probing humans “pushing passages” with no obvious end in sight, and second, the coordinated and skilled use of tools by explorers working in teams. Here, humans define both the scale and perspective of cartographic representations. But bodies slithering along passages make lines, too. This paper simultaneously considers lines of lead on paper and traces of bodies in the earth as a way to think of exploration and mapping as emergent engagements. This case powerfully illustrates the ontogenic nature of maps, highlighting the (re)production of social relations that continually brings them into being along with the environment that engenders these engagements. Finally, cave exploration and mapping illustrate the limits of our vision and technologies to grasp and order nature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".