Saying what we mean, meaning what we say: Managing miscommunication in archaeological prospection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In North America, archaeological prospection has recently undergone a surge in popularity, resulting in higher visibility for both scientific and fringe narratives. This has been partially due to increasingly sensationalized media articles that promote the use of technology to locate overgrown and subsurface features in the landscape. The heightened profile of the field and increasingly sensitive contexts in which it is applied (e.g., locating potential unmarked graves) has expanded the discipline beyond its usual settings where typical archaeological prospection rhetoric and narratives are applied. In this paper, we explore how the presentation of archaeological prospection can impact descendant communities and their burial and cultural spaces. We identify rhetoric, discourse and narrative as key considerations that have resulted in the twisting of interpretations to support fringe narratives. We present two case studies: (1) denialism surrounding unmarked graves at former Indian Residential Schools and (2) the reinterpretation of Indigenous spaces by Graham Hancock's Ancient Apocalypse . We draw upon these seemingly disparate examples as evidence that ambiguity in scholarly communication and ‘certainty’ in fringe communication can both be used to the detriment of Indigenous and other descendant communities in various ways that we term pseudoarchaeological colonialism . Finally, we recommend strategies on how to disseminate results in non‐harmful ways and confront the wrongful usage of archaeological prospection.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it