Tracing Images, Shaping Narratives: Eight Decades of Rock Art Research in Chile, South America (1944–2024)
Bibliographic record
Abstract
80 years of Chilean rock art research, from its early descriptive stages in the 1940s to the present-day integration of relational ontologies, archaeometric techniques, and interdisciplinary perspectives, is reviewed. 562 publications are analysed, covering four major regions: the Arid North, Semi-Arid North, South-Central, and Southernmost Chile. Drawing from a systematically constructed corpus, we trace the evolution of research questions, theoretical orientations, and methodologies over time, with attention to regional trends and institutional dynamics. Results reveal a gradual shift from typological classification toward more complex approaches addressing mobility, landscape, coloniality, visual agency, and human/non-human relationships. The Arid North emerges as the primary centre of innovation, while southern regions remain in exploratory stages despite recent advances. Comparison with global research trajectories shows how Chile’s situated approaches—marked by decentralisation, theoretical pluralism, and critical reflection—contribute to decolonial and southern perspectives in rock art studies. Rather than reproducing hegemonic models, Chilean scholarship offers alternative epistemologies rooted in context-specific materiality and historical processes. The review highlights the potential of Chilean rock art research to expand the theoretical and methodological horizons of the discipline, positioning it as a fertile field for dialogue with contemporary archaeology and global visual studies.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.024 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".