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Record W2977751378 · doi:10.1002/fee.2105

Stool pigeon parrots

2019· review· en· W2977751378 on OpenAlexaboutno aff
Adrian Burton

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2019
Typereview
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsLuckTreasureHistoryArt historyArtLawGenealogyTheologyPhilosophyArchaeologyPolitical science

Abstract

fetched live from OpenAlex

…and the murderer is identified because the victim's parrot pipes up with vital incriminating evidence just at the right moment. That old, unbearable cliché! And the idea is strictly for the birds, right? Well, of course it is. Isn't it? Hmmm, Polly wanna murder mystery (Figure 1)? B Hollis; CC BY SA 2.0 Halifax, Massachusetts, February 15, 1874: a cold evening for a cold-blooded triple murder. William Sturtevant, out of luck and in debt, had hatched a plot to solve all his financial problems in one go: kill his aged granduncles Thomas and Simeon Sturtevant, and take their life savings. Farmers Thomas and Simeon had amassed a pretty penny in their time, and rumor had it that they kept their fortune in the house they shared. They didn't trust the banks. Now in their twilight years, the unmarried brothers were looked after by their housekeeper Mary Buckley, who lived in the adjoining cottage. William may have knocked on his granduncles’ door, or maybe he just bided his time outside, knowing Thomas would at some point come out to tend his cows. It would be their last meeting. William beat Thomas to death with a birch sled stake. He then bludgeoned Mary to death too; no witnesses, no loose ends. Finishing off bedbound Simeon would then have been an easy task. Though William couldn't find his granduncles’ treasure, he did manage to make off with a few hundred bucks, and the detectives on the case soon became aware of the ne'er-do-well's new purchasing power. According to the Spring 2014 Hanson Historical Society Newsletter (https://bit.ly/2ZzLnX3), they then matched a boot print at the crime scene with William's dirtied footwear. But more bizarre evidence was to come. The newsletter reads (corrected): “According to Wells Elliott, the photographer and eye witnesses to the investigation, Mary Buckley's parrot, Captain Kidd, when confronted by Sturtevant who was brought to the murder house in Halifax by the investigators in the case, cowered in the corner of his cage and cried ‘Murder Murder, Help Help!’ ” So much for no loose ends. It's difficult to believe Captain Kidd really uttered his mistress’ last words, but this is not the only time a parrot has apparently helped put someone in the slammer. Agra, India, February 20, 2014: Neelam Sharma was tragically slain by an unknown, knife-wielding assassin in her home. The intruder silenced her barking pet dog in the same manner. The police were stuck for leads, but one soon came from the family parrot, Heera. The Times of India reported how the victim's husband Vijay Sharma noticed that whenever his nephew Ashutosh [Goswami] visited the house – or even when his name was mentioned – the bird began to screech. After Sharma informed the police of this strange behavior, Ashutosh was arrested and duly confessed his crime. Similarly, in 2017, a Michigan county jury found Glenna Duram guilty of killing her husband, Martin Duram, by shooting him five times. Mr Duram's ex-wife took in his African gray parrot, Bud, who, according to the press, started reproducing an exchange in two voices, ending in what was likely Martin Duram's last plea: “Don't…shoot!” The prosecution, however, had enough evidence without requiring Bud to testify. Perhaps they thought he'd break down under cross-examination. While it is not beyond belief that parrots, having witnessed a violent event, might thereafter show fear toward the aggressor, is it likely they can recite a victim's final phrase? After all, they'd only get one shot at learning it. “I suppose it is possible, but I have seen no evidence of it in my own work with natural parrot vocalizations”, says student of parrot talk Tim Wright, a professor of animal behavior at New Mexico State University (Las Cruces, NM). “We'd have to keep track of everything a bird heard and reproduced throughout its life to rule out that an apparent case of one-shot learning wasn't just an instance of the bird repeating something it heard long ago.” Wright had earlier pondered the same kind of question after reading an account of a Brazilian parrot who, after screeching “Mama, police!” to warn its drug-dealing owners of a police raid, was taken into custody (https://nbcnews.to/2Vuq4YM). “The scenario seems implausible, unless the police were regularly driving through the neighborhood within sight of the parrot and the criminals screamed out this phrase each time”, he continued. “I'm not prepared to testify on behalf of prosecutors who wish to establish the validity of parrots as witnesses in a murder case. I would, however, be willing to testify on behalf of the Brazilian parrot on his suitability for bail. I trust him not to fly the coop.” I once knew a parrot that shouted out “Dark!” every time his owner switched off the light in the hallway where the bird lived. He swore he'd never taught him to do that. I'm not sure if I believe that either. But who knows? Mysterious birds, parrots. Adrian Burton

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.341
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.3410.126

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.

Opus teacher head0.041
GPT teacher head0.329
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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