Who is King of Sarawak’s Rainforest? An insight to Sarawak’s land corruption led by its Chief Minister and his family
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
Malaysia’s 13th General Elections were hopes of many to be the turning point of change, breaking Barisan Nasional’s (BN or National Front) 56 years of governance. BN in recent years had been plagued with allegations of corruption and cronyism. Land grabs in the state of Sarawak, exposed an intricate and systematic corruption that happens in all levels of government in Malaysia. The perils of the rainforest in Sarawak are uncovered through a corrupt systematic mass deforestation through the governance of its Chief Minister Taib Mahmud. Was Malaysia’s latest election successful in dethroning Taib and his family out of their political powers? Taib holding several portfolios puts him in immense political and economic power. For more than 30 years, Taib has made use of his various ministerial roles to methodically harvest the state’s natural resources and amassing a personal fortune of USD $15 billion. The first family of Sarawak too has their share in Taib’s fortunes. Kickbacks, corrupt land deals, evasion of Malaysian tax and the service economy of corruption were true and evident in the family’s dealings. Taib’s eldest daughter, Jamilah Taib and her husband Sean Murray, well known socialites in Ottawa, Canada play a major role in the slow death of Sarawak’s rainforest and indigenous tribes. One woman, Clare Rewcastle Brown who manages Sarawak Report and Radio Free Sarawak is determined to bring down the supreme rule of Taib and his family. Her media outlets aim “… to provide that platform and to offer an alternative vision of justice, transparency and a fairer future in Sarawak.”
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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