Lukewarm in Paradise: A Mormon “Poi Dog” Political Journalist's Journey into Hawaii Politics
Bibliographic record
Abstract
BackgroundThis paper describes a lifelong journey in journalism which began in Canada and includes the U.S. mainland and Hawaii.The journey provided the author a unique perspective on the politics of Hawaii as seen during the many years the author lived here.This paper includes an appendix which lists and briefly describes 66 members of the Church of Jesus Christ of Latter-day Saints whom the author has known personally or written about in newspapers, or historical articles.This convenience sample is taken from more than 500 elected politicians and government officials the author interviewed, reported on, or wrote about in scholarly articles, books or newspapers in Canada, Utah, Pennsylvania and Hawaii.Though the author's background in political writing as well as journalism and journalism education spans two countries, four states, and nearly 50 years, this paper primarily focuses on Hawaii politics, particularly the period from 1964 to 1981 when the author was employed as a reporter for the Honolulu Star-Bulletin (1964-69), as administrative assistant to the Senate Minority (1969-1977) and as coordinator for the Marine Advisory Program at the University of Hawai'i (1977-1981).As part of his responsibilities in the LDS Church, the author also originated the Hawaii Record-Bulletin in 1967.This LDS publication was patterned after the Catholic Herald and was mailed to Hawaii's media, government officials, and libraries.The author served as reporter, editor, and liaison between regional Priesthood leaders and the faculty/staff at BYU-Hawaii who published it.The paper's name was changed in 1984 to Hawaii LDS News, under which title the paper existed until it was stopped in 1993.(Unfortunately, today the LDS Church has no such publication to serve as a historical resource of its people and events.)It is from this fundamental source of information (that communicated political as well as spiritual information) that much of the information in this paper was gleaned.Inasmuch as the author wrote many of the political stories and editorials, the data may be considered a primary source.The author also recently conducted a number of personal and telephone interviews with many friends and associates in the media since returning to Hawaii after an absence of 24 years.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.007 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".