The settlement of Polynesia : a computer simulation
Bibliographic record
Abstract
For two centuries people have argued about how the multitudinous islands of Polynesia, flung over some twelve million square miles of ocean and separated by hundreds of miles from the nearest continental coasts, came to be discovered and settled by a single people at a time when navigators of the "civilized" world scarcely ventured willingly beyond the sight of land. Much writing and research have focused attention on the subject in recent years. Now, in a new approach to the question, the authors of this volume report on their use of computer techniques to provide new answers to some of the problems that are central to the controversy. The research project they report upon is of two-fold interest - first, for the light it throws on the riddle of the settlement of Polynesia, and, second, as an innovative demonstration of how computer technology may be applied to a wide variety of research in the social and physical sciences. The authors devised a computer program which simulated Pacific voyaging in its many aspects and variations. Data about winds, currents, islands, and many other pertinent matters were incorporated in the program. Using this model they conducted experiments which showed the outcomes of hypothetical voyages representing many possible variations which real voyages might embrace. The authors describe the experiments and discuss the results and conclusions, illustrating them with numerous maps and cartograms. Computer-drawn maps are included in an appendix. Michael Levison is a member of the department of computer science at Queen{u2019}s University, Kingston, Ontario, Canada, R. Gerard Ward is a professor of human geography at the Australian National University, Canberra, and John W. Webb is a professor of geography and associate dean for social sciences at the University of Minnesota.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".