People, Animals, Protected Places, and Archaeology: A Complex Collaboration in Belize
Bibliographic record
Abstract
The authors of this chapter direct the Stann Creek Regional Archaeology Project (SCRAP), featuring a multi-year, multi-site, multidisciplinary program of archaeological research along the south-eastern margins of the Maya Mountains, Stann Creek District, Belize. While we and our team members most frequently direct our academic efforts in an attempt to reconstruct and understand the complicated suite of developmental processes, experiences, and life histories of the inhabitants of this region more than 1000 years ago, this ancient past represents only one of the two dominant spatio-temporal and socio-political contexts with which we engage on a regular basis. In this chapter, we shift our focus to the interactions with present-day individuals, communities, and institutions that structure our archaeological work. For some perspective, we will discuss the history of the development of the Cockscomb Basin Wildlife Sanctuary and connected forest reserves—totaling some 1011 km2 of nominally ‘protected’ space—and ongoing co-management organization and use relationships with adjacent Indigenous Maya communities. We frame this development within the United Nations Declaration on the Rights of Indigenous Peoples, and supplement historical records with informally gathered impressions from local rights-holders and stakeholders, as well as through our own experiences and observations. We conclude by returning to the subject of our own operations within the region to highlight how SCRAP has attempted to learn from this history—particularly with respect to co-management and community engagement—and to propose areas for improvement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".