Bibliographic record
Abstract
This chapter provides Cote d&s;Ivoire profiles, including key information about the relevant corporate sustainability and responsibility (CSR) history, country-specific issues, trends, research, education and leading organizations. Cote d&s;Ivoire is an ethnically diverse country with over 70 native languages spoken. Traditional export goods of Cote d&s;Ivoire include agricultural commodities such as cocoa, coffee, cotton, rubber, palm oil, pineapple, banana, tuna and tropical woods. Cote d&s;Ivoire is facing significant environmental problems. Conflict diamonds from the north of Cote d&s;Ivoire, which are banned by the Kimberly Process, continue to appear on the world market, notably in the United Arab Emirates, according to the non-governmental organisation Partenariat Afrique Canada. Cote d&s;Ivoire is facing tremendous challenges concerning its state of public health. The regulation and protection of the environment in Cote d&s;Ivoire is under the jurisdiction of the Ministry of Housing, Living Conditions, and the Environment. Nestle is among the largest companies operating in Cote d&s;Ivoire.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.137 | 0.026 |
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 source (direct Gemma or distilled Codex), 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".