Bibliographic record
Abstract
Geotechnologies are increasingly prominent, accessible, and interactive. Hand-held devices can localize one’s current geographic position with an unsettling precision. With the emergence of such mapping apparatuses, GPS-informed practices have proliferated. They redefine our engagement with space/place in ways that anthropologists need to attend to. Geocaching, a popular activity happening across the world, provides an ethnographic example of interest whose resonance extends beyond its practice. This paper focuses on the ways in which spaces have the potential to become meaningful in specific ways for those engaging in this practice. I adopt an autobiographical approach, which I carefully unpack, following my movement in the context of geocaching in Athens to gain an embodied understanding of the place-making possibilities afforded by the activity. It is argued that emplacement –that is, a situated body-mind-environment relationship– can result from a particular form of sensory and affective engagement with and negotiation of a device-environmental dialectic. To this end, I sketch a critique of geographic apparatuses such as maps, coordinates, and GPS devices, informed by the ironic double-bind geocachers must navigate. While they require geotechnologies to situate the approximate location of a geocache, they also risk being deceived by incongruence between reductive and life-annihilating “map spatialities” and “the realities on the ground” (in all their sensuous and affective possibilities). My work also demonstrates, in part, that geographic apparatuses may be thought of as cultural technologies, as are the processes and practices by which we use, evaluate, and ultimately translate them. It is through this experience of movement and sensory negotiation between technology and environment, I contend, that places can meaningful for geocachers in new and specific ways.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| 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".