{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/369472"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/369472","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"New methods to answer old questions: A study of London infant and child mortality at the turn of the twentieth century","abstract":"This thesis has strived to understand the inequalities of infant and child mortality in London at the turn of the twentieth century (1895-1911), and to add to the debate on the historical infant mortality decline. Previous studies in this field have been plagued with limitations driven by data availability and quality. Now, historical demographers are turning to new technologies and methods – including big microdata, multilevel analysis and text-mining – to overcome these past issues. This thesis has contributed to the growing literature on new sources and methods, whilst remaining grounded in traditional historical demography debate, and has focused on one urban area: London. London was – and still is – a ‘mosaic of communities’ with its inhabitants’ experiences varying vastly. It is also a city with considerable historical data availability, therefore providing huge potential for comparative analysis. By applying a mixed method approach that utilises both quantitative and qualitative sources, the infant and child mortality experiences of individual Londoners and aggregate London registration sub-districts have been compared. The thesis can be broken down into three main sections. The first section has interrogated the quality of occupational and social class coding of the big microdata project, I-CeM, before comparing and contrasting different data sources/methods in order to determine the accuracy of aggregate infant mortality rates. The second section has employed multilevel modelling techniques to visualise and understand the inequalities – by social class, place, and otherwise – of individual-level indirectly estimated child mortality. The third section added depth and nuance to the quantitative results through both the close-reading, and text-mining, of the Medical Officer of Health Reports for two contrasting areas within London: Bethnal Green and Wandsworth. In the conclusion, the results of the quantitative and qualitative analyses have been triangulated to form robust conclusions and highlight areas suitable for further research. Overall, this thesis has contributed to the body of evidence supporting the role of the ‘Health of Towns’ Movement and Female Empowerment theories of infant mortality decline. Additionally, it has contributed to knowledge on infant and child mortality inequalities associated with social class, place, migrant-status, the employment of mothers and the influence of Women Sanitary Inspectors.","abstract_html":"This thesis has strived to understand the inequalities of infant and child mortality in London at the turn of the twentieth century (1895-1911), and to add to the debate on the historical infant mortality decline. Previous studies in this field have been plagued with limitations driven by data availability and quality. Now, historical demographers are turning to new technologies and methods – including big microdata, multilevel analysis and text-mining – to overcome these past issues. This thesis has contributed to the growing literature on new sources and methods, whilst remaining grounded in traditional historical demography debate, and has focused on one urban area: London. London was – and still is – a ‘mosaic of communities’ with its inhabitants’ experiences varying vastly. It is also a city with considerable historical data availability, therefore providing huge potential for comparative analysis. By applying a mixed method approach that utilises both quantitative and qualitative sources, the infant and child mortality experiences of individual Londoners and aggregate London registration sub-districts have been compared. The thesis can be broken down into three main sections. The first section has interrogated the quality of occupational and social class coding of the big microdata project, I-CeM, before comparing and contrasting different data sources/methods in order to determine the accuracy of aggregate infant mortality rates. The second section has employed multilevel modelling techniques to visualise and understand the inequalities – by social class, place, and otherwise – of individual-level indirectly estimated child mortality. The third section added depth and nuance to the quantitative results through both the close-reading, and text-mining, of the Medical Officer of Health Reports for two contrasting areas within London: Bethnal Green and Wandsworth. In the conclusion, the results of the quantitative and qualitative analyses have been triangulated to form robust conclusions and highlight areas suitable for further research. Overall, this thesis has contributed to the body of evidence supporting the role of the ‘Health of Towns’ Movement and Female Empowerment theories of infant mortality decline. Additionally, it has contributed to knowledge on infant and child mortality inequalities associated with social class, place, migrant-status, the employment of mothers and the influence of Women Sanitary Inspectors.","abstract_has_math":false,"creators":["Rafferty, Sarah"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Reid, Alice"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-12-22","date_published":"2022-12-22","updated_at":"2026-07-22T22:24:18Z","subjects":["Child mortality","Digital humanities","Historical demography","Infant mortality","Text-mining"],"languages":["eng"],"rights":[],"rights_urls":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/e32e59c6-c20e-473b-a2c2-2acc284a370c/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"identifier_entries":[{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000322863598"],"render_values":[{"text":"0000-0003-2286-3598","href":"https://orcid.org/0000-0003-2286-3598","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.109261","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Reid, Alice"]},{"key":"dc:creator","label":"Author","values":["Rafferty, Sarah"]},{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000322863598"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2022-12-22"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/369472"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Child mortality","Digital humanities","Historical demography","Infant mortality","Text-mining"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/e32e59c6-c20e-473b-a2c2-2acc284a370c/download","https://www.rioxx.net/licenses/all-rights-reserved/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.109261"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/dec3b8a2-156e-48c6-92a8-a662f781311b/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis has strived to understand the inequalities of infant and child mortality in London at the turn of the twentieth century (1895-1911), and to add to the debate on the historical infant mortality decline. 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The first section has interrogated the quality of occupational and social class coding of the big microdata project, I-CeM, before comparing and contrasting different data sources/methods in order to determine the accuracy of aggregate infant mortality rates. The second section has employed multilevel modelling techniques to visualise and understand the inequalities – by social class, place, and otherwise – of individual-level indirectly estimated child mortality. The third section added depth and nuance to the quantitative results through both the close-reading, and text-mining, of the Medical Officer of Health Reports for two contrasting areas within London: Bethnal Green and Wandsworth. In the conclusion, the results of the quantitative and qualitative analyses have been triangulated to form robust conclusions and highlight areas suitable for further research. Overall, this thesis has contributed to the body of evidence supporting the role of the ‘Health of Towns’ Movement and Female Empowerment theories of infant mortality decline. 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The first section has interrogated the quality of occupational and social class coding of the big microdata project, I-CeM, before comparing and contrasting different data sources/methods in order to determine the accuracy of aggregate infant mortality rates. The second section has employed multilevel modelling techniques to visualise and understand the inequalities – by social class, place, and otherwise – of individual-level indirectly estimated child mortality. The third section added depth and nuance to the quantitative results through both the close-reading, and text-mining, of the Medical Officer of Health Reports for two contrasting areas within London: Bethnal Green and Wandsworth. In the conclusion, the results of the quantitative and qualitative analyses have been triangulated to form robust conclusions and highlight areas suitable for further research. Overall, this thesis has contributed to the body of evidence supporting the role of the ‘Health of Towns’ Movement and Female Empowerment theories of infant mortality decline. 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