Imperial Intersections: Archaeologists, War and Violence. Comment.
Bibliographic record
Abstract
This is a commentary on a series of papers presented in the Imperial Intersections: archaeologists, war and violence session at the 2007 Annual Meeting of the Society for American Archaeology.The session addressed issues surrounding archaeology, war and violence and the ethical responsibilities of archaeological practitioners.The papers in this volume have created more questions than answers, but as with all ethical scenarios, I was inspired to think and to examine critically aspects of archaeology that may have eluded past contemplation.In attempting to find commonalities and themes in the submissions I realized that almost every paper is concerned with the production of knowledge-how much access should there be; who should have access to knowledge; how should knowledge be disseminated; and when and if the knowledge should be reproduced.The central debate of ''in whose best interest is this knowledge produced'' is also explored in this review?________________________________________________________________ Re ´sume ´: Ce qui suit est un commentaire portant sur plusieurs articles pre ´sente ´s par les recoupements impe ´riaux: la session sur les arche ´ologues, la guerre et la violence tenue en 2007 a `l'Annual Meeting of the Society for American Archaeology (rencontre annuelle de la socie ´te ´se consacre ´e a ` l'arche ´ologie ame ´ricaine).La session s'est concentre ´e sur les proble `mes d'arche ´ologie, de guerre et de violence et les responsabilite ´s e ´thiques des praticiens arche ´ologiques.Les articles de ce volume ont souleve ´davantage de questions que de re ´ponses, mais a conside ´re ´tous les sce ´narios e ´thiques.J'ai e ´te ´pour ma part amene ´a `penser et a `examiner de fac ¸on critique des aspects de l'arche ´ologie qui peuvent avoir e ´chappe ´par le passe ´.En tentant de trouver des similitudes et des the `mes soumis j'ai re ´alise ´que presque tous les articles se sont focalise ´s sur la production de la connaissance-quel degre ´d'acce `s devait e ˆtre de ´ploye ´; comment cette connaissance devrait-elle e ˆtre disse ´mine ´e; et a `la fois quand et si cette connaissance devait e ˆtre reproduite.Le de ´bat central de « qui aurait le plus grand inte ´re ˆt a `acce ´der a ` cette connaissance » est e ´galement explose ´dans cette interview.
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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 | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.063 | 0.044 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".