Guns, gender and petroleum: a critical analysis of the underlying dynamics of Timor-Leste’s development trajectory
Bibliographic record
Abstract
This article examines the underlying political economy context of the uneven development outcomes in post-conflict Timor-Leste. We use a modified version of a structural political economy approach that is situated in a Gramscian understanding of the state-society relationship. This approach conceptualises development as a process of historically specific class-based and gender-based contestations over the distribution of resources that result in particular forms of socio-political orders maintained through a combination of institutional and ideological mechanisms of wealth generation. Our analysis of whose interests have been prioritised and marginalised in post-independence Timor-Leste is based on a systematic examination of three major factors: regulation of class relations, organisation of gender relations, and the governance of the petroleum industry. We conclude that despite some important improvements in the formation of formal democratic institutions in Timor-Leste, the processes of the distribution of power and access to resources remain far from being inclusive prioritising a class-based group of male-dominant elites that manipulates institutions to advance their interests and use a hegemonic gender ideology to justify and maintain these existing unequal arrangements in the prevailing socio-political order. Thus, the development outcomes in Timor-Leste are strongly connected to the political-economic processes from a larger historical perspective.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".