Representation and materiality in archaeology: A semiotic reconciliation
Bibliographic record
Abstract
In this introduction to the special edition, we argue that the theories of philosopher Charles Sanders Peirce have the potential to bridge some of the deepest divides in archaeology. We also demonstrate that the adoption of an extreme ‘anti-representational’ position in thing-centred turns in the discipline is misguided, as scholars recognize diverse modalities of representation beyond symbols and immaterial signifiers. By combining the insights of Peircean semiotics, assemblage theory, and new approaches inspired by the ontological turn, we rehabilitate representation as a fundamental material process in the exercise of agency and the making and transformation of ‘meaningfully constituted worlds.’ Mobilizing theories on semiotic ideologies in particular, we further contend that the material worlds assembled through representational processes can often be harmful, unjust, contradictory, challenged and potentially reconfigured. Ultimately, as a semiotic science in its own right, archaeology must devise new ways to analyse the mediated representations of the past subjects they study. The diverse articles of this issue have made an important contribution exploring this central problem in archaeological research.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| 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".