Bibliographic record
Abstract
This paper will explore the perspectives and narratives developed by three different sets of Chinese investors in Papua New Guinea (PNG): investors in the retail, mining and construction sectors. It is estimated that 90 percent of new Chinese private investors in the PNG retail sector hail from Fuqing, a coastal community in Fujian Province with a long history of transnational migration. Larger state-owned mining ventures and construction companies draw on a more disparate workforce, even though they are headquartered in Beijing. All three sets of investors face different degrees of stigmatization from their competitors, the media and different Chinese and local actors. Based on interviews with Chinese investors in PNG and China, and drawing on Chinese scholarly studies, this paper will explore the interaction of these three groups of investors with Chinese state and non-state actors, and evaluate how this shapes the process of "localization." The paper will examine how relations with state and non-state actors in PNG are evolving over time, as both groups find ways to "get things done" in a country where mainland Chinese investors have a short history of engagement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".