Finger Fluting in Prehistoric Caves: A Critical Analysis of the Evidence for Children, Sexing and Tracing of Individuals
Bibliographic record
Abstract
Abstract Finger flutings are channels drawn in soft sediments covering walls, floors and ceilings of some limestone caves in Europe and Australia and in some cases date as far back as 50,000 years ago. Initial research focused on why they were made, but more recently, as part of a growing interest in the individual in the past, researchers began asking questions about who made them. This shift in direction has led to claims that by measuring the width of flutings made with the three middle fingers of either hand, archaeologists can infer the ordinal age, sex and individuality of the ‘fluter’. These claims rest on a single dataset created in 2006. In this paper, we undertake the first critical analysis of that dataset and its concomitant methodologies. We argue that sample size, uneven distribution of sex and age within the sample, non-standardised medium, human variability, the lack of comparability between an experimental context and real cave environments and assumptions about demographic modelling effectively negate all previous claims. To sum, we find no substantial evidence for the claims that an age, sex and individual tracing can be revealed by measuring finger flutings as described by Sharpe and Van Gelder (Antiquity 80: 937-947, 2006a; Cambridge Archaeological Journal 16: 281–95, 2006b; Rock Art Research 23: 179–98, 2006c). As a case study, we discuss Koonalda Cave in southern Australia. Koonalda has the largest and most intact display of finger flutings in the world and is also part of a cultural landscape maintained and curated by Mirning people.
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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 | 0.017 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| 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".