Archaeological knowledge in the era of scientific mediation: issues in the mass media and museums
Bibliographic record
Abstract
The present Special Issue is a part of a scientific research and mediation program. It is especially related with the question of cultural dissemination of scientific elements in the archaeological museum. This program is the fruit of a Greek-Canadian collaboration team set up in recent years by experienced and young researchers from the University of Quebec in Montreal (UQAM) and the University of Patras. The program was supported by the Social Sciences and Humanities Research Council (SSHRC) with a grant from its Connection program (2019-2021-Archeology in the era of scientific mediation). This financial aid enabled our team to support events and outreach activities, such as seminars and knowledge mobilization initiatives and lead to the publication of this Special Issue Archaeological knowledge in the era of scientific mediation: issues in the mass media and museums.
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.023 | 0.056 |
| Scholarly communication | 0.057 | 0.033 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 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".