From mines to minds: addressing the skills gap in Sierra Leone
Bibliographic record
Abstract
Subject area International business, Strategic management Study level/applicability BA and MA; courses: International business, Management courses with special focus on emerging and developing countries, Intercultural management, Strategic management. Case overview Freetown, Sierra Leone, West Africa, June 2013 – Representatives of the London Mining Corporation and Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH were discussing the details about the official launch of the From Mines to Minds project. The From Mines to Minds project consisted of two components technical, vocational and educational training at St. Joseph's and functional adult literacy for people who could not benefit from the upgrade of St. Joseph's in 17 communities around the mine site. Each of them had committed 200,000 euros to the project. While the mining company favored an early launch due to internal and external pressures, the development agency evaluated that they needed to have a consolidated program before advertising it locally and nationally. This joint decision on the official launch revealed more structural issues in the “fit” between these two organizations in this cross-sectoral partnership designed to contribute to local and national sustainable development. Expected learning outcomes The purpose of the case is twofold. The first aim is to introduce students/participants to the challenges that arise when entering into a cross-sectoral partnership with another organization in a development project. The second aim is to expose students to the operational, business and strategic challenges related to operating in the volatile local and national context of a least developed economy. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email: support@emeraldinsight.com to request teaching notes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".