Thirty-Two Years of Integrating Archaeology and Heritage Management in Belize: A Brief History of the Belize Valley Archaeological Reconnaissance (BVAR) Project’s Engagement with the Public
Bibliographic record
Abstract
Since its inception in 1988, the Belize Valley Archaeological Reconnaissance (BVAR) Project has had two major foci, that of cultural heritage management and archaeological research. While research has concentrated on excavation and survey, the heritage management focus of the project has included the preservation of ancient monuments, the integration of archaeology and tourism development, and cultural heritage education. In this paper, we provide a brief overview on the history of scientific investigations by the BVAR Project, highlighting the project’s dual heritage management and research goals. This background offers the basis in which to discuss the successes and challenges of the project’s efforts in cultural heritage management and public engagement, particularly in early conservation efforts, in its training and educational efforts, and its ongoing outreach activity. We emphasize the need to train Belizeans as professional archaeologists and conservators, to serve as the next generation of advocates for Belize’s heritage management. We offer some ideas on how research projects can make significant contributions to heritage education and preservation in the developing world.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".