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Record W3215635487 · doi:10.1007/s10437-021-09464-4

Record-Making, Research, and Removal: Mitigating Impacts on Rock Art in a CRM Context in Southern Africa—the Case of the Metolong Dam, Lesotho

2021· article· en· W3215635487 on OpenAlex
Charles Arthur, Peter Mitchell, Lara Mallen, David Pearce, Adelphine Bonneau, Frans Prinsloo, Rethabile Mokachane, Pulane Nthunya, Sheriff Mothopeng, Rachel King, Jess Meyer, Luíseach Nic Eoin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAfrican Archaeological Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicArchaeology and Rock Art Studies
Canadian institutionsUniversité de Sherbrooke
FundersSocial Sciences and Humanities Research Council of CanadaNatural Environment Research CouncilNational Research FoundationUniversité du Québec à MontréalWorld Bank Group
KeywordsRock artContext (archaeology)DocumentationArchaeologyRadiocarbon datingCultural heritageWork (physics)GeographyHistoryEngineering

Abstract

fetched live from OpenAlex

Abstract This paper reports on the steps taken to mitigate the impact of the Metolong Dam (Lesotho) on the rock art present within the catchment of its associated reservoir. Mitigation took four major forms: comprehensive survey and documentation, including both photography and tracing; pigment characterization and radiocarbon dating; exploration of the ongoing significance of rock art as a form of living heritage for people living in the vicinity; and removal of selected panels for permanent safekeeping. These steps are placed within the wider context of other cultural heritage management projects in Africa and their success evaluated. Recommendations are made for how similar work should be undertaken in future.

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)0.005
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.118
GPT teacher head0.399
Teacher spread0.281 · 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