Recollections and Reflections on the Reimer Twin Case in Canada: Interview with Dr H. Keith Sigmundson/Tribute and Twin Research Review: Remembering John L. Hopper; Nonhuman Primate Twinning/Human Interest: <i>The Accidental Twins</i> film; Different Looking Identical Twin Newborns
Bibliographic record
Abstract
Abstract Dr H. Keith Sigmundson co-authored a seminal article (with the late Dr Milton Diamond) that revealed the truth about a highly controversial twin case. Specifically, the genitals of an infant male monozygotic twin were accidentally destroyed during a medical procedure performed to alleviate his difficult urination. The child’s parents were advised to physically and psychologically transform their twin son into a girl. Occasional reports about the case indicated that the plan was successful, but some members of the medical community were doubtful. An interview with Dr H. Keith Sigmundson, for the purpose of obtaining his unique perspective on this case, is presented. The interview is followed by a tribute to our late twin research colleague, Dr John L. Hopper, of Melbourne, Australia. A review of research on nonhuman primate twinning, an overview of a 2024 documentary film, The Accidental Twins, and a story of different looking identical twin newborns are also provided.
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 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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.022 |
| Insufficient payload (model declined to judge) | 0.003 | 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".