UFOs, ETs, and Alien Abductions: A Scientist Looks at the Evidence by Don Donderi
Bibliographic record
Abstract
Many books about UFOs appear each year, yet few of these books are worth reading; UFOs, ETs, and Alien Abductions is one of those few. The author, Don Donderi, holds a doctorate in psychology and spent most of his career at McGill University in Montreal as a professor, dean, and researcher. His specialties are human visual perception and memory, with several books and more than one hundred research papers and technical reports to his credit. He began to read about UFOs when he was ten years old. The interest has stayed with him throughout his life and motivated him to investigate several sightings as the opportunities arose. In 1968 he participated in a review of occupant cases as a consultant for the National Investigations Committee on Aerial Phenomena (NICAP), then the leading U.S. civilian UFO investigations organization. In the 1990s, when abductions dominated ufology, he consulted on how to interpret the results of a Roper Poll designed to uncover the prevalence of abduction-like experiences in the general public, and participated in major meetings such as the 1992 Abduction Study Conference held at MIT. He further lent his psychological expertise to a personality test for separating simulated abduction claims from honest experiential reports, and to an experiment that compared symbols reported by abductees with symbols imagined by non-abductees.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".