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Record W3041473647 · doi:10.18192/potentia.v6i0.4413

The Destruction of Mali's Cultural Heritage

2015· article· en· W3041473647 on OpenAlexaffvenue
Fionndwyfar Colton

Bibliographic record

VenuePotentia Journal of International Affairs · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsLootingFraming (construction)Cultural heritagePoliticsPolitical sciencePolitical economyIndependence (probability theory)Government (linguistics)Organised crimeCriminologyLawSociologyHistoryArchaeology

Abstract

fetched live from OpenAlex

In Mali, and throughout West Africa, ongoing illicit trafficking movements and violent conflicts have necessitated a call for new protective measures and policies to protect cultural heritage. Traditional strategies of customs regulation and restriction on the antiquities market have been previously based on economic and legal issues enmeshed in trafficking networks and transnational crime processes. However, these do not reflect the realities of Malian daily life, nor do they go beyond the onedimensional stance framing the actions of looters and traffickers as a facet of these processes. What is ignored are the underlying motivations for looting and illicit antiquities trafficking and how these motivations are affected by, and enacted through, the ever shifting socio-political climate that has been Mali’s system of government since its independence from the French Sudan in 1960. This paper explores the realities of looting throughout Mali, ongoing debates concerning the representation of Malian antiquities in the transnational art trade, and the ways in which both national and international bodies have attempted to thwart ongoing heritage destruction.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.008
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.265
Teacher spread0.235 · 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
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
Published2015
Admission routes2
Has abstractyes

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