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Record W4406323173 · doi:10.1111/epic.12170

Friction between Reticence and Narrative in Local and Global Interconnections along the Ethical Canadian Diamond Supply Chain

2023· article· en· W4406323173 on OpenAlexaboutno aff
Linda Armano

Bibliographic record

VenueEthnographic Praxis in Industry Conference Proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeDiamondSupply chainBusinessAestheticsSociologyMaterials sciencePhilosophyArtLiteratureComposite materialMarketing

Abstract

fetched live from OpenAlex

This research analyses, through ethnographic research, the cultural interpretations of the global storytelling of Canadian ethical diamonds given by different subjects, belonging to diverse sociocultural and economic contexts, including staff of mining companies, indigenous communities, jewellers, and consumers. The study took place at the two ends of the diamond supply chain, in the Canadian Northwest Territories, where the mines and mining companies are located, and in two jewellery stores in Milan and Bologna, that sell Canadian diamonds. Introducing the concept of the Process of Argumentative Aphasia I highlight how the discourses of the participants in the research on Canadian ethical diamonds were becoming increasingly metaphorically unpronounceable and, therefore, misaligned with the official storytelling as I approached the mining context; whereas moving towards the sales contexts, the argumentative contents of the jewellers' and consumers' speeches were more aligned with the contents of the global advertising narratives on diamonds mined in Canada.

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)0.006
metaresearch head score (Gemma)0.014
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.456

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0280.048
Scholarly communication0.0170.006
Open science0.0020.008
Research integrity0.0020.003
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 head0.024
GPT teacher head0.256
Teacher spread0.232 · 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
Published2023
Admission routes1
Has abstractyes

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