Inka Interaction at Caleta Vitor, Northern Chile: Evidence from Archaeological Textiles
Bibliographic record
Abstract
Our understanding of Inka expansion continues to develop with new research further cementing the idea that the Inka’s expansionary tactics were targeted and agile, specifically enacted to achieve coercive control over populations, resources, and specialist craft expertise. The nature of Inka influence at Caleta Vitor has not yet been established, however, the data now strongly suggest that the population was entangled in a complex negotiated process commonly undertaken by the Inka in new territories. This paper contributes to our understanding of Inka interaction at Caleta Vitor with new data from archaeological textiles that demonstrate Caleta Vitor’s Imperial connections. Nuestra comprensión de las estrategias de expansión inka continúa desarrollándose con nuevas investigaciones. Estas consolidan aún más la idea acerca que las tácticas de expansión fueron dirigidas y puestas en práctica específicamente para lograr un control coercitivo sobre las poblaciones, recursos y trabajo artesanal especializado. La naturaleza de la influencia inka en Caleta Vitor (norte de Chile) aún no ha sido establecida, sin embargo, los datos sugieren que la población estaba involucrada en un complejo proceso de negociación emprendido por los inkas en nuevos territorios. Este artículo contribuye a nuestra comprensión de la interacción inka en Caleta Vitor con nuevos datos obtenidos de textiles arqueológicos, para reconsiderar las conexiones del imperio en esa localidad y sus impactos en la región.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".