Broken Trust: Greed, Mismanagement & Political Manipulation at America’s Largest Charitable Trust
Bibliographic record
Abstract
Princess Bernice Pauahi Bishop was the largest landowner and richest woman in the Hawaiian kingdom. Upon her death in 1884, she entrusted her property--known as Bishop Estate--to five trustees in order to create and maintain an institution that would benefit the children of Hawai‘i: Kamehameha Schools. A century later, Bishop Estate controlled nearly one out of every nine acres in the state, a concentration of private land ownership rarely seen anywhere in the world. Then in August 1997 the unthinkable happened: Four revered kupuna (native Hawaiian elders) and a professor of trust-law publicly charged Bishop Estate trustees with gross incompetence and massive trust abuse. Entitled "Broken Trust," the statement provided devastating details of rigged appointments, violated trusts, cynical manipulation of the trust’s beneficiaries, and the shameful involvement of many of Hawai‘i’s powerful. \n \nNo one is better qualified to examine the events and personalities surrounding the scandal than two of the original "Broken Trust" authors. Their comprehensive account together with historical background, brings to light information that has never before been made public, including accounts of secret meetings and communications involving Supreme Court justices.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".