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Enregistrement W2553538504 · doi:10.1353/llt.2016.0092

Lives in Transition: Longitudinal Analysis from Historical Sources ed. by Peter Baskerville and Kris Inwood

2016· article· en· W2553538504 sur OpenAlexvenueaboutno aff
Lisa Dillon

Notice bibliographique

RevueLabour / Le Travail · 2016
Typearticle
Langueen
DomaineHealth Professions
ThématiqueIndigenous Studies and Ecology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCensusHistoryForegroundingGenealogyEthnic groupWhite (mutation)SociologyMedia studiesPopulationAnthropologyDemographyArt

Résumé

récupéré en direct d'OpenAlex

Reviewed by: Lives in Transition: Longitudinal Analysis from Historical Sources ed. by Peter Baskerville and Kris Inwood Lisa Dillon Peter Baskerville and Kris Inwood, eds., Lives in Transition: Longitudinal Analysis from Historical Sources (Montréal and Kingston: McGill-Queen’s University Press 2015) The edited volume Lives in Transition: Longitudinal Analysis from Historical Sources has arrived at a propitious moment when academic researchers are foregrounding the critical importance [End Page 382] of early life conditions on later-life outcomes at the same time that public concern for intergenerational social inequality has intensified. This collection touches on both issues, and more. The chapters in this volume are grouped into four themes – transnational migrations, mobility in the rural world, mobility in the urban world, and ethnicity and war – and encompass 19th and 20th-century Canada, Australia, New Zealand and the United States. While most of the chapters address the lives of free white male groups such as farmers, industrial labourers, and migrating settlers, some chapters address marginalized populations such as convicts and Aboriginals. This book is particularly notable for its integration of methodological innovations with path-breaking evidence on historical life course patterns. This volume serves as an excellent primer on various approaches to constructing linked data sets, usually via census-to-census linkage, but often with the integration of other historic sources. Some of the studies relied upon high-performance computing and machine-learning to develop automatic record linkage programs. Luiza Antonie, Peter Baskerville, Kris Inwood and J. Andrew Ross linked women and men between the 1871 and 1881 censuses to study Canadian occupational mobility while Gordon Darroch linked census microdata from 1861 and 1871 Ontario to study factors conditioning entry into farming. In his analysis of factors predicting movement and persistence in rural Perth County, Ontario, 1871–1881, Baskerville focused on 1871 residents in a smaller geographic unit but then searched for each resident across Canada and the United States in the censuses of 1880/1881; by doing so, Baskerville situated his population at the crossroads of micro- and national history. Kenneth M. Sylvester and Susan Hautaniemi Leonard traced farm operators and their households over time, drawing upon both personal and agricultural schedules of the Kansas census from selected communities. Other scholars broadened their studies by tapping into complementary resources. In his study of US social mobility between 1900 and World War II, Evan Roberts used a survey of Chicago working-class families conducted in 1924 and 1925, linking survey respondents backward to the 1920 census and forward to the 1930 census. John Cranfield and Inwood drew upon the personnel records of the Canadian Expeditionary Force (cef) 1914–1918, linking them to the 1901 Canadian census. Sherry Olson linked Montréal residents enumerated in the 1881 census to the 1901 census, but also attached addresses and rental values from the municipal tax roll to her data, consulted Catholic and Protestant marriage records to help with the matching effort, and used gis to estimate distances between households. By linking aboriginals and mixed-race men in the cef records back to the 1901 Canadian census, Allegra Fryxell, Inwood, and Aaron van Tassel discovered that “Aboriginal participation in the war was considerably more extensive than has been recognized.” (270) The two studies of British convicts transported to Tasmania drew upon British convict records which meticulously recorded extensive details of convicts’ origins, physical characteristics, and experience under sentence, as well as surgeon-superintendent voyage journals. Rebecca Kippen and Janet McCalman used this source to identify a unique set of “character” variables in terms of convicts’ behaviour under sentence; the researchers then searched across a wide variety of genealogical sources for the destiny of each convict. Lenihan also used crowd-sourced genealogical information, a register of 6,243 immigrants of Scottish birth arriving [End Page 383] in New Zealand before 1921. Kandace Bogaert, Jane van Koeverden and D. Ann Herring consult largely qualitative sources, including recruitment materials, church records, advertisements and letters in newspapers and army records, to understand the origins and spread of influenza in 1918 in the Polish Army Camp at Niagara-on-the-Lake. The various papers demonstrate two basic approaches: a national-level or provincial/state-level study which uses...

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)0,009
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil0,080

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,017
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0040,013
Études des sciences et des technologies0,0040,003
Communication savante0,0080,010
Science ouverte0,0020,004
Intégrité de la recherche0,0020,009
Charge utile insuffisante (le modèle a refusé de juger)0,0150,009

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 Opus0,017
Tête enseignante GPT0,276
Écart entre enseignants0,260 · 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'étudeQualitatif
Domainenon disponible
GenreEmpirique

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
Publié2016
Routes d'admission2
Résumé présentoui

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