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Record W3212977895 · doi:10.21810/strm.v13i1.299

Boom and Bust Archaeology

2021· article· en· W3212977895 on OpenAlexaffvenueabout
Andrew Kacey Thomas

Bibliographic record

VenueStream Interdisciplinary Journal of Communication · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBustBoomIndigenousValue (mathematics)Resource (disambiguation)HistoryArchaeologySociologyEngineeringComputer science

Abstract

fetched live from OpenAlex

As a discourse analysis of historical resource assessment documents and interviews with professional archaeologists, this study aims to inspect and critique the production of value in the Alberta historical resource value (HRV) system. The system of evaluation for historical value creates what can be described as a presence-absence model of archaeological significance that limits the ability for archaeologists to interpret and subjectively determine the historical value of materials. In addition, current systems often rely on a contractual relationship between archaeologists and industry to produce these reports, and rarely incorporate indigenous perspectives of significance. With a focus on the assumptions and functional result of HRIA assessments, we can examine the repercussions of the contemporary archaeological evaluative model within Alberta. A goal of this nascent assessment is to provide the opportunity for evaluation of a system that largely exists below the surface of public interest but has vast implications for future access to shared historical resources.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.650
Threshold uncertainty score0.704

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0110.012
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.025
GPT teacher head0.337
Teacher spread0.313 · 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

Citations0
Published2021
Admission routes3
Has abstractyes

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