Shifting Networks and Community Identity at Tell Tayinat in the Iron I (ca. 12th to Mid 10th Century B.C.E.)
Bibliographic record
Abstract
The end of the 13th and beginning of the 12th centuries B.C.E. witnessed the demise of the great territorial states of the Bronze Age and, with them, the collapse of the extensive interregional trade networks that fueled their wealth and power. The period that follows has historically been characterized as an era of cultural devolution marked by profound social and political disruption. This report presents the preliminary results of the Tayinat Archaeological Project (TAP) investigations of Iron I (ca. 12th to mid 10th century B.C.E.) contexts at Tell Tayinat, which would emerge from this putative Dark Age as Kunulua, royal capital of the Neo-Hittite kingdom of Palastin/Patina/Unqi. In contrast to the prevailing view, the results of the TAP investigations at Early Iron Age Tayinat reveal an affluent community actively interacting with a wide spectrum of regions throughout the eastern Mediterranean. The evidence from Tayinat also highlights the distinctively local, regional character of its cultural development and the need for a more nuanced treatment of the considerable regional variability evident in the eastern Mediterranean during this formative period, a treatment that recognizes the diversity of relational networks, communities, and cultural identities being forged in the generation of a new social and economic order.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".