Trends in ceramic assemblages from the Northwest Quarter of Gerasa/Jerash, Jordan
Bibliographic record
Abstract
Past peoples left behind preciously little for us to reconstruct their daily lives and histories. However, some types of archaeological material stand the test of time better than others thanks to their durability and ubiquity, and foremost among them: the ceramic evidence. Pottery often serves as a proxy for the reconstruction of a variety of aspects of a past life: the wealth of city inhabitants, the function of spaces (Smith, 1987), cultural transmission between craftsmen (Coto-Sarmiento et al., 2018) or trading interactions (Brughmans and Poblome, 2016). However, to take full advantage of the wealth of information that can be derived from pottery evidence it is essential to use robust analytic methods establishing the full distribution in ceramic use and discard and its evolution over time. Here, we present a comprehensive data analysis of ceramic material coming from the Northwest Quarter of Jerash, present-day Jordan. It is one of the first examples of full quantification of an archaeological site of this age in the region. More than 625 000 pieces of pottery have been collected, recorded and analysed. We describe the process of data preparation, cleaning, exploratory analysis and statistical examination as well as visualisation. All steps of data analysis have been undertaken in the Python scripting environment making the process entirely transparent, reproducible and reusable for other researchers. We showcase how full quantification combined with quantitative analysis can lead to detection of significant trends in pottery evolution over centuries and enable robust comparative studies in the region and beyond.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".