A critical response to Halley's (2022) ‘Audubon’s diary transcripts were doctored to support his false claim of personally discovering Lincoln’s Sparrow Melospiza lincolnii (Audubon, 1834)’
Bibliographic record
Abstract
In a recent article (Bull. Brit. Orn. Cl. 142: 329–342), Matthew Halley contended that John James Audubon (1785–1851) lied about his discovery of Lincoln's Sparrow Melospiza lincolnii (Audubon, 1834) during his 1833 Labrador expedition. Extracts from the naturalist's journal, published after his death in a biography prepared by his widow, Lucy (1787–1874), states that he was aboard ship ‘Drawing all day’ when the specimen was collected by one of his assistants. Consequently, Halley submitted that Audubon’s claim in the Ornithological biography to having first sighted the bird was fabricated and that his granddaughter Maria R. Audubon (1843–1925) doctored her alternate version of the journal to be consistent before she destroyed the original. However, Halley overlooked critical facts, including evidence that Lucy’s manuscript was compiled and edited by others; the published work contained numerous errors; and the journal entries for the previous two weeks were misdated and sometimes conjoined from multiple days, proving that her journal was not a faithful transcription of the original.
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 | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.022 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.017 | 0.039 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".