Bibliographic record
Abstract
Abstract This article provides an introduction to the theme issue “Archaeology of Service.” We explore how performing service in archaeology articulates with the concepts and practices of community-based archaeology, collaborative archaeology, and the Archaeologies of the Heart projects and their larger purposes of approaching work through a lens of social and environmental justice. We introduce seven articles that describe working in communities around the world, including the Bininj of the Gundjeihmi Aboriginal Corporation in the Northwest Territory of Australia; the Bunun of the Lakulaku River Basin in Taiwan; the Passamaquoddy Nation in Maine (USA); people from 21 First Nations in the province of Ontario, Canada; the diverse communities of Oklahoma (USA); the African American community in Bolivar, Texas (USA); and the people of San Cristóbal Island in the Galápagos Islands, Ecuador. The articles are tied together by the common theme of collaborative work that is built through relationships of trust and is conducted in ways that strive to change the institutional and educational structures in which archaeology is practiced.
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".