Towards an Evaluation-Based Framework of Collaborative Archaeology
Bibliographic record
Abstract
Abstract Collaborative archaeology is a growing field within the discipline, albeit one that is rarely analyzed. Although collaborative approaches are varied and diverse, we argue that they can all share a single methodological framework. Moreover, we suggest that collaborative archaeology projects can be evaluated to determine the variety among projects and to identify the elements of engaged research. We provide two case studies emphasizing project evaluation: (1) inter-project evaluation of community-engagement in British Columbia archaeology and (2) intra-project evaluation of co-management archaeology projects in Western Australia. The two case studies highlight that project evaluation is possible and that a single framework can be applied to many different types of projects. Collaborative archaeology requires analysis and evaluation to determine what facilitates engagement to further the discipline and to create better connections between archaeologists and community members. The discussed case studies illustrate two shared methods for accomplishing this. The paper argues that collaborative approaches are necessary for advancing archaeological practice.
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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 | 0.212 | 0.137 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.016 | 0.010 |
| Science and technology studies | 0.008 | 0.060 |
| Scholarly communication | 0.030 | 0.025 |
| Open science | 0.010 | 0.018 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".