Asian Investment in the Rural Industries of Papua New Guinea: What's New and What's Not?
Bibliographic record
Abstract
One part of the Australian colonial legacy in Papua New Guinea (PNG hereafter) is the Australian government's attempt to forge partnerships with foreign companies in different economic sectors in order to lay the economic foundations for rural development in the newly independent nation. American and Australian capital was invited to develop the mining industry, European capital to develop the oil palm industry, and Japanese capital to develop the forest industry. Nowadays, the Australian government seems to have forgotten its late colonial enthusiasm for this form of state capitalism, and its aid to PNG is largely framed by the neo-liberal policy prescriptions which the World Bank was able to impose on the PNG government through a sequence of structural adjustment programs beginning in 1990. However, members of PNG's national political elite have persistently sought refuge from this economic orthodoxy through their engagement with Asian governments and companies. In this paper I examine the way in which changing political and economic conditions have affected the actual pattern of Asian investment in PNG's forestry and agriculture sectors, and the way in which different stakeholders have responded to this changing pattern of investment. Despite the prevalence of a policy narrative which holds Asian investors responsible for the corruption of PNG's political institutions when mineral resource booms liberate national politicians from the constraints of Western economic orthodoxy, I show that Asian investment in these two sectors has taken several different forms, and there is no simple sense in which PNG's national economy and political system are subject to a concerted takeover by Asian business interests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".