The Search for a Paradigm in Archaeology Evolutionary Theory and the "Selectionist" School of Thought
Bibliographic record
Abstract
According to evolutionary archaeology (the "selectionist" school of archaeological theory) the archaeological record can be explained in terms of generic Darwinian processes of evolution. Evolution is seen as the differential persistence of cultural traits and as the differential reproductive success of individuals in result of the cultural traits they possess. However, one of the major criticisms of evolutionary archaeology is concerned with the absence of a defined unit of selection. Evolutionary biologist Richard Dawkins and others have suggested that the same generic process as biological evolution governs culture change and that culture evolves as a result of the differential replication of cultural units, the memes, that play an analogous role as genes. If this is so, it is suggested that the unit of selection that might be lacking in evolutionary archaeology is the meme. Since memetics (the study of memes as cultural replicators) is a theory of cultural change it has the potential to provide the explanatory framework for the temporal and spatial patterns of archaeological phenomena. Despite its potential, memetics seems to introduce Lamarckian processes of evolution in Ihe culture medium, which are not very explanatory. The purpose of this article is to show the potential of generic evolutionary processes in explanations of culture change and discuss the major problems involved in this theoretical approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.054 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".