Industrial policy environments and the flourishing of African multinational enterprises
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Research on African organizations has focused on the influence of environmental factors in organizational effectiveness. However, increasing concerns about challenges in Africa and how they negatively affect organizational outcomes have necessitated leveraging the “positive turn” of organizational scholarship to advance a perspective of how industrial policies can permit Africa-originated multinational enterprises (A-MNEs) to flourish. We propose a multilevel model in which the industrial policy environment comprised of agency and policy development positively impacts A-MNE flourishing, a composite index of human, environmental, and economic flourishing. This relationship is mediated by industrial policies – labor, trade, infrastructure, and resources – and moderated by policy fit, relevance, and timeliness. Overall, we shift the old paradigm of organizational outcomes represented by organizational effectiveness to a new paradigm represented by organizational flourishing. This new paradigm seems more appropriate for Africa, which is bedeviled by unusual challenges that limit effectiveness. We discuss empirical testing of the model and implications for managers.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it