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Enregistrement W3154473680 · doi:10.1111/rssa.12698

John Haigh 1941–2021

2021· article· en· W3154473680 sur OpenAlexaboutno aff
Charles M. Goldie

Notice bibliographique

RevueJournal of the Royal Statistical Society Series A (Statistics in Society) · 2021
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueForecasting Techniques and Applications
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésScholarshipClassicsGrammar schoolLawSociologyHistoryArt historyPolitical sciencePedagogy

Résumé

récupéré en direct d'OpenAlex

John Haigh, who died on 9 March 2021 aged 79, was the pre-eminent populariser of probability for his time.Through many publications and media appearances, he perfected the rare art of explaining subtle concepts and calculations to those who would claim no mathematical knowledge.Though his audiences may not have realised it, his standards were high; he never shielded them from a calculation they could do or a concept they could master.He recounted with delight how a colleague had reported her stockbroker husband saying to her at midnight 'I can't come to bed just yet dear: I have to finish one of the calculations in Dr Haigh's book'.John was born on 31 December 1941 and grew up as an only child in Skelmanthorpe, a village near Huddersfield in Yorkshire, where his father worked in the woollen mill and his mother in the canteen.His Methodist upbringing gave John a valuable objectivity in later life as an expert on gambling: gambling was frowned upon, but winning through gambling was especially deprecated.From grammar school ('three hours homework every night'), he won a State Scholarship to read mathematics at Brasenose College Oxford, gaining first-class honours and a University Prize in 1963.Soccer provided a social as well as sporting escape from the general rugby-playing ex-public-school milieu, and John rose to win a Blue, playing for his university against Cambridge at Wembley (where Oxford lost 5-2).Students then were not supposed to gain both a Blue and a First, as the sporty and scholarly subpopulations of undergraduates were largely distinct.D. G. Kendall left Oxford during John's undergraduate years to be the first holder of the Chair of Mathematical Statistics at Cambridge, and his reputation was such that it was no surprise for bright students to follow him to the other place and join the re-invigorated Statistical Laboratory.With a government grant, John started as one of DGK's research students in 1963, enrolling at Gonville and Caius College.He was unlucky in the existence of a link between Caius and his Oxford College, as without that he would have joined Kendall's college, the recently founded Churchill, which looked after its many graduate students, whereas the old colleges neglected them.The young Mr Kingman, as Sir John Kingman then was, took over some of Kendall's research students in 1964.John Haigh was among them, and when Kingman left for the University of Sussex, it was natural for him to follow, though remaining registered for a Cambridge PhD.From his research studentship, John progressed to a lectureship at Sussex, where he stayed for the rest of his career, though spending summers in the 1970s at Melbourne and Stanford, and the year 1983-1984 at the University of Guelph in Canada.At Sussex, he was promoted to Senior Lecturer in 1989 and to Reader in 1993.Retirement was a progress through many stages, and John was still giving a lecture course to first-year undergraduates in his 70s.John's thesis was on random equivalence relations, a combinatorial topic but with a biological motivation; early papers were thus on applications of probability to questions in biology and genetics.Collaboration with the biologist John Maynard Smith led to five important joint papers, laying down the mathematical theory of concepts such as evolutionarily stable strategy, which underpin much of later thinking about evolution.Subsequent work, mostly single-authored but interspersed with joint papers with various co-authors, established John as an expert on combinatorial applied probability,

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,088
Score d'incertitude au seuil0,293

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0050,001
Communication savante0,0040,002
Science ouverte0,0010,002
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0880,040

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,050
Tête enseignante GPT0,354
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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