"The miner's canary" - what the maritime heritage crisis says about archaeology, cultural resource management, and global ecological breakdown
Bibliographic record
Abstract
This dissertation investigates the maritime heritage crisis as it exists on the Pacific Northwest Coast of North America, emphasizing the Salish Sea region of Washington State, USA, and British Columbia, Canada. Worldwide, maritime landscapes are undergoing unprecedented change resulting in physical, biological, and cultural problems of “wicked” proportions. To focus conversation, the maritime heritage crisis is defined here as heritage site loss resulting from amenity migration and sea level rise. Rapid, unsustainable population growth (coastal sprawl) and anthropogenic climate change (global warming) are key drivers of contemporary coastal change, thus, arguably, heritage destruction. In Northern America, the response to coastal change has been resource management, elevating the concepts of “resourcism” and “management” as central elements of coastal change discourse. In this dissertation, I examine the response of archaeology/cultural resource management (CRM) to coastal change. I survey coastal change threats and impacts, focusing on Indigenous maritime heritage landscapes because they are especially sensitive to coastal change and the primary context for Northern American archaeology/CRM. To assess heritage conservation and the success of CRM in the Pacific Northwest, I present a case study of the shíshálh (Sechelt) First Nation’s traditional territory in British Columbia’s amenity-rich Sunshine Coast. I discuss the shíshálh Nation’s heritage stewardship approach and detail coastal change impacts in three areas within the Nation’s territory. In addition to future sea level rise, the impact of amenity migration or “sea change” on Indigenous heritage is demonstrated to be significant. Indigenous maritime heritage landscapes are highly threatened, contested and politicized places, tied up in issues of nationalism, colonialism, sovereignty and, increasingly, cultural survival. By focusing on social power and domination, a critical heritage studies approach exposes resource management as a technology of government promoting and permitting the ideology of growth, development and progress. Archaeology/CRM is therefore implicated in both the destruction of Indigenous heritage landscapes and the psychosocial consequences of that destruction, and is thus part of the problem, not the solution. An example of the “miner’s canary,” the shíshálh Coast study offers important lessons about heritage stewardship in the late modern era of consumer capitalism.
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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 | 0.000 | 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 | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".