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Record W2913035358 · doi:10.1558/jca.33578

Direct Actions and Archaeology

2019· article· en· W2913035358 on OpenAlexaff
Bill Angelbeck, Johnny Jones

Bibliographic record

VenueJournal of Contemporary Archaeology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsDouglas College
Fundersnot available
KeywordsParallelsIndigenousPoliticsHistoryColonialismRelevance (law)ArchaeologyAction (physics)Environmental ethicsEthnologyPolitical scienceLawEcology

Abstract

fetched live from OpenAlex

Direct action has been a key tactic of many social and political movements throughout history. Here, we consider the relevance of direct actions for archaeology, both for heritage protection and other forms of archaeological activism. We also discuss collaborative and community-based archaeologies as direct relationships and actions that can help prefigure the non-colonial relationships between archaeologists, indigenous peoples, and heritage. In the process, we provide a case history of Lil’wat peoples, who continue to exert control over their unceded territory and heritage from development. In recent decades, the Lil’wat Peoples Movement used direct actions in logging road blockades, to stop developments from damaging and destroying archaeological sites, of which Johnny Jones was a member. We also describe our collaborations over the last decade in investigating sites in various capacities. In so doing, we also consider the parallels between indigenous and anarchist approaches in anarcho-indigenist thought.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0080.087
Scholarly communication0.0110.009
Open science0.0010.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.042
GPT teacher head0.302
Teacher spread0.260 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations4
Published2019
Admission routes1
Has abstractyes

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