Knowledge Exchange, Public Affairs
Bibliographic record
Abstract
Abstract: KNOWLEDGE EXCHANGE “Approaches to Material of the Past in Jordan: Highlighting the Seventh World Archaeological Congress” by Shatha Abu‐Khafajah, Elizabeth Konwest and Dru McGill PUBLIC AFFAIRS ETHICAL CURRENTS |“Waste's Messy Challenge to Anthropology: Waste Water in Cairo's Ezbet Khairallah” by Tessa Farmer Morag M Kersel is contributing editor of“Ethical Currents,”the AAA Committee for Ethics column in Anthropology News. RESEARCH ON POLICY |“Reframing ‘Racial Profiling’” by Luis FB Plascencia Vasiliki Neofotistos and Anette Nyqvist are contributing editors of Research on Policy, the AN column of the AAA Interest Group for the Anthropology of Public Policy (IGAPP). VIEWS ON POLICY |“Anthropologists‐in‐the‐Making: Finding Our Way to an Anthropological Filter” by Marie Schaefer Pam Puntenney is contributing editor of Views on Policy, the AAA Interest Group for the Anthropology of Public Policy column in Anthropology News. HUMAN RIGHTS FORUM |“When Ethics Meet Human Rights” by Gretchen Schafft Miriam Ticktin is contributing editor of “Human Rights Forum,” the AAA Committee for Human Rights column in Anthropology News. Keywords: Archaeology, waste, race, policy, human right
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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.031 | 0.024 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.124 | 0.027 |
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".