It’s What’s Inside that Counts: Developing a paste group typology in Belize
Bibliographic record
Abstract
The ceramic assemblage at the Classic Period Maya site of Alabama, Belize is poorly preserved and fragmentary. Most of the pottery cannot be classified using standard type-variety approaches, which privilege decoration and surface treatment. The nature of the Alabama ceramic assemblage requires a classification system organized by paste wares, as opposed to incorporating paste composition as a modal or analytical unit that crosscuts types and wares, as this is the only attribute that can be reliably evaluated across all contexts. We identified and systematically described paste groups as a first step toward a typology organized by ceramic paste wares. We analysed 100% of ceramics from settlement surface collection at the site, including non-diagnostic samples, using a scaffolded approach that integrates macroscopic observations, Dino-Lite USB microscopy, and thin section petrography. This approach facilitates the analysis of pottery from all contexts, regardless of the degree of preservation. Incorporating paste composition into classification schemes provides important data on pottery production traditions and the people responsible for their production, which cannot be determined from stylistic analyses alone. We established five new paste groups indicative of local and non-local pottery production. Our approach to ceramic classification provides a method that can be applied to any archaeological site, regardless of the prevailing classification system in place, and is especially relevant to sites with poorly preserved ceramic assemblages dominated by non-diagnostic sherds.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".