Ethical product havens in the global diamond trade: Using the Wayback Machine to evaluate ethical market outcomes
Bibliographic record
Abstract
Who benefits from ethical product markets? While most ethical products (e.g. fair trade and eco-certified products) are intended to benefit marginalized communities and vulnerable ecosystems, the reality is that the geographic preferences exhibited by so-called ethical markets may, in fact, reinforce global inequities rather than remedy them. It can be difficult to evaluate the outcomes of ethical product markets, however, because we are often limited to data from a small number of industries with widely used standards and certifications. This research pilots a new methodology, using an online archive—the Wayback Machine, to evaluate shifts in countries' ethical market share, focusing on the evolution of the ethical diamond market over the past 20 years. The ethical diamond market is an interesting case because it began specifically as a competition among countries of origin, with Canadian officials and diamond producers trading on Canada's reputation to position Canada as an ethical product haven in opposition to conflict diamonds from Africa. Yet, Canada's early ethical monopoly has been contested on multiple fronts, and this article focuses on the following questions: To what extent has the contestation over Canada's ethical monopoly actually changed the ethical diamond market? Specifically, how much market share have different ethical alternatives gained and lost over time? And, what does this tell us about the governance and development outcomes of the market? The results show that while the market has diversified over time, it is still largely not benefiting the most marginalized diamond producing countries and communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".