When Past and Present Collide: The Ethics of Archaeological Stewardship
Bibliographic record
Abstract
The Archaeological Institute of America's (1999) code of professional standards requires that archaeologists “work actively to preserve the [archaeological] record in all its dimensions and for the long term” and “give due consideration to the interests of others” in their work. At the AIA's 2006 annual meeting in Montreal, participants in a session entitled “When Past and Present Collide: The Ethics of Archaeological Stewardship” explored the implications of these obligations for the conduct of archaeology and suggested ways for archaeologists to engage with stakeholder collaboration, site preservation, and political aspects of archaeology. Presentations by Lynn Meskell, Michael Galaty, Roger Atwood, Daniel Shoup, Ian Hodder, and Lyra Monteiro included case studies from South Africa, Peru, Albania, and Turkey. They examined when archaeologists should take sides in political conflicts over archaeology, how economic and social issues that are unrelated to archaeology can be decisive in site preservation efforts, whether acceptance of universal heritage values should be a precondition for inclusion of nonarchaeologists in stewardship planning, and when the actions of archaeologists themselves can be harmful to site preservation efforts. Rather than being prescriptive, these contributions offered a variety of perspectives and suggestions for integrating stewardship and collaboration into archaeological research.
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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 | 0.080 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.143 |
| Scholarly communication | 0.028 | 0.025 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".