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North American Cultural Heritage Law

2020· book-chapter· en· W3092055192 on OpenAlexaboutno aff
Derek Fincham

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachCultural heritageConventionPolitical scienceLaw enforcementEnforcementCultural heritage managementLaw

Abstract

fetched live from OpenAlex

Abstract This concluding chapter offers a comparative perspective on the key components of contemporary cultural heritage law in North America. The region’s collective tangible and intangible cultural heritage has an array of legal and policy tools to safeguard it for future generations, though coordination between the three nations involved would benefit from increased cohesiveness. The primary legal mechanisms to prevent illicit movement are restrictions on removing archaeological materials; declarations of ownership for some or all of this material; export restrictions; and the ultimate enforcement of these protections both domestically and abroad. All three countries in North America have made this body of law a priority. The chapter then looks at the law enforcement efforts, international outreach, and treatment of specific objects of cultural heritage in Mexico, Canada, and the USA. It also describes the relationship of these North American States with the World Heritage Convention and UNESCO’s Underwater Cultural Heritage Convention.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.894
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.004
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0290.003

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 head0.028
GPT teacher head0.183
Teacher spread0.154 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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