International businesses and the challenges of poverty in the developing world : case studies on global responsibilities and practices
Bibliographic record
Abstract
We live in a globally interconnected but economically divided world where internationally linked businesses can play a significant role in helping and/or obstructing the development of impoverished countries. Through a series of case studies, this volume examines what can be learned, both positively and critically, from the experiences of selected internationally connected firms in Nigeria, Uganda, Ghana, Vietnam, Guyana, and the Nunavik region of northern Canada. This book begins with a set of reflections on the strategies firms might adopt so that they develop both their own assets as well as those of the areas in which they operate. A team of more than two dozen researchers from the developed and developing countries conducted the research on which the essays on this and subsequent volumes are based. Dr Frederick Bird from Concordia University in Montreal directed the overall research project.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".