Win-win or new imperialism? Public-private partnerships in Africa mining
Bibliographic record
Abstract
One of the most significant elements of globalisation is the way in which the reshaping of the public-private divide is transforming the relationship between state and economy. In industrialised economies, there is a growing commodification and privatisation of public services, undertaken through the establishment of public private partnerships. State policy is becoming increasingly ‘market-driven’, managing national politics in such a way as to adapt to the pressures of transnational market forces (Leys, 2001). In developing economies, structural adjustment has removed the state as the principal agent of development, while private agencies are playing an increasingly public role as they engage in public service delivery. These include non-profit organisations (churches and NGOs) and for-profit caregiving and educational institutions (van Rooy & Robinson, 1998). In the political arena, the discourse over donor-defined democratisation has also meant a larger political role for a differentiated set of private agents, in the name of civil society participation, prompting Schmitz & Hutchful (1992) to call this a recipe for ‘free markets and free votes’.
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.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".