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Record W2947443189 · doi:10.1515/opar-2019-0013

The Archaeological Impacts of Metal Detecting

2019· article· en· W2947443189 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOpen Archaeology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPresumptionDichotomyLegislationArchaeologyArchaeological recordSimple (philosophy)HistoryComputer scienceData scienceLawPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract In a comment on two recent articles on the archaeological impacts of metal detecting, this paper advocates clearer and more valid measures of those impacts and more nuanced classification of the legal and cultural environments in which metal detecting takes place. The need to rely on open-source, online data for transnational analysis makes the former challenging but not impossible. Using the example of Canada, the paper shows that jurisdictional and other complexities make simple “permissive” and “restrictive/prohibitive” dichotomies unhelpful, and suggests using multivariate analysis that accounts for such factors as presumption of ownership, locations of metal detecting, availability of finds reporting, and whether heritage legislation concerns artifacts or only sites. This is essential for development of sound, evidence-based policy on the metal-detecting hobby.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.032
GPT teacher head0.293
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it