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UID:calendarize-defense-of-the-doctoral-dissertation-janis-krumins
DTSTAMP:20260413T164213Z

DTSTART:20260430T070000Z
DTEND:20260429T210000Z
    
SUMMARY:Defense of the doctoral dissertation: Jānis Krūmiņš
DESCRIPTION:Scientific supervisors of the work:\nAssoc. Prof.\, Dr. geogr. Raimonds KasparinskisProf.\, Dr. geogr. Oļģerts Nikodemus\nReviewers:\nDr. Donatas Burneika (Vilnius University\, Lithuania)Dr. Nissa Finney (University of St Andrews\, United Kingdom)Dr. Jānis Brizga (University of Latvia)\nAbstract\nThis doctoral thesis is a thematically unified collection of scientific publications examining the role of internal migration in population redistribution across Latvia. It analyses the geographical distribution of migrants at different spatial scales using georeferenced data and spatial analysis methods\, and applies regression analysis to examine the population composition of in-migrants. The findings are based on annual registered migration data (2011–2021) and individual-level census data (2000\, 2011\, 2021). A key novelty of the study lies in the application of spatial autocorrelation at a regular grid cell level\, extending its use in migration research\; whereas the regression analysis contributes to the theoretical literature on the role of migration in shaping the territorial differentiation of human capital.
X-ALT-DESC;FMTTYPE=text/html:<p><strong>Scientific supervisors of the work:</strong></p>\n<ul><li>Assoc. Prof.\, Dr. geogr.<strong> Raimonds Kasparinskis</strong></li><li>Prof.\, Dr. geogr. <strong>Oļģerts Nikodemus</strong></li></ul>\n<p><strong>Reviewers:</strong></p>\n<ol><li>Dr. Donatas Burneika (Vilnius University\, Lithuania)</li><li>Dr. Nissa Finney (University of St Andrews\, United Kingdom)</li><li>Dr. Jānis Brizga (University of Latvia)</li></ol>\n<p><strong>Abstract</strong></p>\n<p>This doctoral thesis is a thematically unified collection of scientific publications examining the role of internal migration in population redistribution across Latvia. It analyses the geographical distribution of migrants at different spatial scales using georeferenced data and spatial analysis methods\, and applies regression analysis to examine the population composition of in-migrants. The findings are based on annual registered migration data (2011–2021) and individual-level census data (2000\, 2011\, 2021). A key novelty of the study lies in the application of spatial autocorrelation at a regular grid cell level\, extending its use in migration research\; whereas the regression analysis contributes to the theoretical literature on the role of migration in shaping the territorial differentiation of human capital.</p>
LOCATION:UL House of Nature\, Room 702
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