The History of Archaeology as Seen Through the Externalism-Internalism Debate: Historical Development and Current Challenges
Bibliographic record
Abstract
While internalism and externalism are nothing more than two categories coined by historians of science during the 1960s (for an introduction to the internalism-externalism debate, see: Basalla 1968; Lakatos 1970; Ben-David 1971; Agassi 1981; Morrell 1981 and Shapin 1992), they are terms often used by historians of archaeology to define the two different interpretations of the history of their discipline (e.g. Meltzer 1989: 17–18; Trigger 2001: 635; Schlanger 2004: 165–166; Trigger 2006: 25; Díaz-Andreu 2007: 4; Kaeser 2008: 10). Why have these terms proven to be so popular?
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".