Above, Beneath, and Within: Collaborative and Community-Driven Archaeological Remote Sensing Research in Canada
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
This thesis investigates the application of geophysics and remote sensing techniques in community-driven and collaborative archaeology research in Canada. While these techniques have become common among some archaeologists, they have yet to be extensively used within the lens of Indigenous archaeology. In the introductory chapters, I present the current Canadian context and review the theory, method and application of these techniques to archaeology. I argue for a reconsideration of how these techniques are applied and interpreted within Indigenous contexts, specifically, where these applications have fallen short and how these techniques impact and are shaped by modern Indigenous communities. I propose a methodological approach that incorporates multiple lines of evidence, Indigenous knowledge, and Indigenous archaeology principles, as a potential ‘middle range’ solution. To illustrate how this approach can be applied with Indigenous communities in Canada, I present the methods and results of three community-driven unmarked grave surveys and two collaborative archaeology projects. Drawing on these case studies, I demonstrate 1) that these techniques are effective at contributing to common community-based research goals in a wide range of sites and environments, 2) there are unique factors present when working with Indigenous communities that need to be reflected in and balanced by research designs, 3) the incorporation of multiple lines of evidence and collaborations with Indigenous communities will result in more holistic, meaningful, and co-produced narratives for communities and researchers, and 4) when framed and designed in an engaged and respectful way, archaeological remote sensing can contribute to modern Indigenous communities’ needs and objectives.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it