The reception of Palaeolithic art at the turn of the twentieth century: between archaeology and art history
Bibliographic record
Abstract
In this paper I focus on the role of art history in early conceptualizations of Palaeolithic art (1860-1930). In the decades around 1900, the formal analysis of Palaeolithic representations was highly inspired by models, theories and concepts first developed by art historians. I consider two main levels of influence. First, the modern distinction between ‘fine arts’ and ‘crafts’ influenced early interpretations of ‘primitive art’, a category that included Palaeolithic representations. Second, art history provided archaeologists with the theoretical background that helped them to interpret prehistoric images. For instance, archaeologists borrowed their terms and concepts from art historians. Moreover, the ‘representational’ and ‘degenerationist’ theories prevalent in art theory during the nineteenth century became the dominant theories to explain the origin and evolution of figurative and abstract representations. I complete this examination on the relationships between art history and archaeology by analyzing the impact of Palaeolithic images in art historical narratives. In particular, I examine the ways in which prehistoric representations were incorporated into the accounts elaborated by art historians during the first half of the twentieth century.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".