Technical Brief 19: Archeological Collections and the Public: UsingResources for the Public Benefit
Bibliographic record
Abstract
Introduction Archeological collections are rich resources for building outreach programs that engage the public, in exploring the depth and diversity of the past. The collections provide building blocks for acquiring skills and knowledge that are useful in modern life by investigating the material evidence of past peoples and learning lessons from their experiences. In these ways, archeological collections open avenues of inquiry for new approaches to old problems and enable professionals to assess the relevance of curatorial practice in contemporary society. Outreach programs have a wealth of material available to them as a result of archeology, perhaps even more than some curators realize. Beyond artifacts, archeological collections can include many other kinds of materials, such as soil samples, photographs, maps, research and excavation reports, project notes, oral histories, ethnographic records, and other information pertinent to an excavation. They tend to be managed by federal and state agencies, tribes, and local constituencies in many kinds of repositories, including libraries, historical societies, parks, museums, colleges and universities, and even private collections. Note, however, that many other places care for archeological materials, including tribal heritage centers and cultural resource management companies. Members of the curatorial staff within the repositories, however, are not necessarily archeologists and may demonstrate a lack of understanding about archeology. This lack of familiarity impedes their ability to explore the full potential of archeological collections for outreach and education. Archeologists and non-archeologists alike must seek creative applications for the collections they curate. Outreach provides an outlet to educate the public and encourage questions about the past and present. Whether well-versed or new to archeology, museum professionals should understand that responsible curation involves making the resources of archeological collections available as a means for everyone to learn about the past. Finding a Purpose for Curation Audiences for Collections Case Studies Nevada State Museum, Carson City, Nevada Maryland Archaeological Conservation Laboratory at Jefferson Patterson Park and Museum, St. Leonard, Maryland Alutiiq Museum and Archaeological Repository, Kodiak, Alaska Archaeology Collection, Bryn Mawr College, Bryn Mawr, Pennsylvania Midwest Archeological Center, National Park Service Conclusion Bibliography Special thanks to
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.249 | 0.200 |
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".