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Enregistrement W800497077 · doi:10.1162/jinh_r_00819

<i>The Dawn of Canada’s Century: Hidden Histories</i>. Edited by Gordon Darroch (Montreal, McGill-Queen’s University Press, 2014) 498 pp. $100.00

2015· article· en· W800497077 sur OpenAlexaffabout
Barry Edmonston

Notice bibliographique

RevueThe Journal of Interdisciplinary History · 2015
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueCanadian Identity and History
Établissements canadiensUniversity of Victoria
Organismes subventionnairesnon disponible
Mots-clésMicrodata (statistics)CensusAmerican Community SurveyGeographyPopulationGenealogyPoliticsRegional scienceDemographyHistorySociologyPolitical scienceLaw

Résumé

récupéré en direct d'OpenAlex

This book, written by many of Canada’s leading historical scholars, sheds new light on a number of topics, including language identity, aboriginal populations, family and household arrangements, immigration, politics, and social class and mobility at the beginning of the twentieth century. Its most important feature is the analysis of historical census microdata. The four introductory chapters deal with census data and methods, the new 1911 census microdata sample, and parallel projects for samples of the 1851/52, 1871, 1881, 1891, and 1901 censuses. In addition to the 1911 census sample, comparable samples are also underway for the 1921, 1931, 1941, and 1951 censuses. The other twelve chapters present an analysis of historical census microdata. All of them analyze 1911 data, but several use other historical data sets. A chapter about Quebec City explores the linkage of individuals over several censuses for the 1871 to 1911 period. About one-half of the chapters examine Canada’s national population. Other chapters deal with subnational populations, including Trois-Rivières, Newfoundland, Quebec City, and Hamilton.The development and availability of census microdata samples has been the basis for improvements in research during the past five decades. The methodological foundation for these new data emerged in the 1930s and 1940s when statisticians provided the theory and methods for survey sampling. By the 1950s, researchers were able to conduct national surveys of 1,000 respondents, with valid inferences about entire populations. Because of new sampling methods, better statistical software, and big advances in computing technology, census microdata has progressed in four stages.First, survey sampling techniques were employed for the first time after the 1960 U.S. census to make data tapes with public-use microdata samples (pums) available. These pums files were either 1-in-1,000 or 1-in-100 (1 percent) samples of individual records—omitting identifiers that could reveal individual identities—with information about age, sex, ethnic origin, nativity, marital status, family relationships, occupation, income, and other data collected in the census. These first pums files proved to be a treasure chest; researchers could, for the first time, prepare their own tabulations rather than depend on tables published by the U.S. Census Bureau. Moreover, researchers could use modern multivariate statistical techniques for the analysis of census microdata. By the end of the 1960s, academic journals routinely included articles with regression and other multivariate analysis of census data.The second major advance occurred when census microdata for several countries became available for comparative analysis. By the 1970s, the census microdata samples for many countries could be used for the study of such topics as the factors associated with international variations of female employment.When researchers realized the value of pums files for several censuses, they began to develop pums files for earlier censuses—the third stage. In the United States, researchers initially took samples from the 1940 and 1950 censuses in order to make longer-term comparisons with existing 1960, 1970, and 1980 censuses. Currently, 1 percent pums files exist for U.S. decennial censuses from 1850 to the present, comprising one of the most valuable quantitative data sets for historical research.We are currently in the midst of a fourth stage—the development of large census-data collections that are both historical and comparative, as evidenced by the pioneering work of ipums-International (https://international.ipums.org/international/), which now includes pums files for 258 censuses from 79 countries. For a comparative study of, say, southern Latin America, ipums-International currently includes sixteenth census pums files for Argentina, Chile, and Uruguay that could be used to analyze trends from the 1960s to the present. The next frontier for census microdata analysis is the comparative study of change over time in, for instance, the determinants of fertility variations, correlates of family structure, and factors affecting the living arrangements of elderly adults.U.S. census microdata files—including individual data with detailed codes for age, country of birth, ethnic origin, and place of residence (though no personal identifiers)—are usually available for public use, as evidenced by their availability for download from ipums-usa (https://usa.ipums.org/usa/). Canadian census data, however, are relatively restricted. Some of it, such as census microdata samples for the 1921 to 1951 censuses, are available only within special limited-access research data centers. Moreover, Canada’s pums are more limited than comparable data in the U.S. and some other countries. For example, information about place of residence is limited to the several-dozen-largest metropolitan areas (compared to several hundred cities of smaller size in the U.S. pums files). Moreover, Canadian public-use data on couples is confined to the ethnic origin of only three categories for husbands and wives—British, French, and other—thus preventing analysis of ethnic intermarriage.pums have several distinctive advantages over files in data centers or other facilities that limit the access and release of data tabulations. Although researchers can prepare tabulations and multivariate analysis with both public-use and restricted data, public-use data offer significant advantages in three situations: (1) Analysis of individual census data often requires supplementing the pums files with other data, including contextual variables like the unemployment rate in a city or town. Public-use data facilitates downloading such information from internet sources and linking contextual variables to individual records. Since restricted-data centers often prohibit internet connections and prohibit researchers from entering with other electronic data, they inhibit the development of new data sets. (2) New data files can be created within a restricted data center, but, at least in Canada and probably other countries, they cannot be removed from the center. Hence, researchers who spend considerable time linking individuals with their spouses, children with their mothers, or adults with information about their household cannot easily share their findings with researchers outside the data center. This problem relates to another particularly important issue—(3) the difficulty of replicating empirical research conducted within a restricted data center because other researchers may not have access to the original or intermediate files.The Dawn of Canada’s Century provides a valuable source of historical evidence about the development of Canada at the beginning of the 1900s. It should appeal to readers and scholars in search of a systematic and stimulating treatment of historical census data.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
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: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,146
Score d'incertitude au seuil0,293

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,006
Études des sciences et des technologies0,0060,003
Communication savante0,0080,003
Science ouverte0,0010,002
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0580,015

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 Opus0,010
Tête enseignante GPT0,215
Écart entre enseignants0,205 · 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
GenreSynthèse

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
Publié2015
Routes d'admission2
Résumé présentoui

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Même revueThe Journal of Interdisciplinary History→Même sujetCanadian Identity and History→Travaux en français237 207→