Quantitative Methods for the Analysis of Medieval Calendars

The article explores the uses of quantitative approaches used in textual scholarship in studying large amounts of medieval hand-written calendars. Calendars are exceedingly numerous among medieval manuscript sources but have been studied surprisingly little in spite of the insights they offer into the values and ideals of the communities using and updating them. Moreover, the study of a large number of calendars helps shape patterns of cultural contacts, for instance. The constant copying and modifying of a medieval calendar is analogous to copying of other manuscripts by hand in the Middle Ages. However, the overall pattern of influences was much more complex than in traditional copying, and new quantitative methods are called for. In this article, we propose three different quantitative methods for the analysis of medieval calendars. They provide a scholar with sound hypotheses on the relationships between a large number of calendars, on the broader context of an individual calendar's contents as well as on the single feasts that can be indicative of the origin of one or several calendars.Peer reviewe

Miten käy yleisosaamisen erikoislääkärien koulutuksessa?

publishedVersio

Research orientation among general practitioners compared to other specialties

Objective The volume of research work done by general practitioners (GP) is modest compared to other specialties. In order to find out reasons for this we examined the current situation concerning research orientation and factors relating to them among Finnish GPs compared to other specialists. Design and setting Data from The Physician 2018 Study were used for our research. The study was undertaken in collaboration with all five medical faculties in Finland and the Finnish Medical Association. It compiled information on physicians` social background, work history and career and research plans as well as their views regarding undergraduate and specialist training, values, and professional identity. Subjects The basic study population comprised all Finnish doctors under 70 years of age (N = 23,131). Questionnaires were sent to doctors born on even-numbered days (n = 11,336). Altogether 5,214 (45.8%) responded. Responses from GPs (n = 796) were compared with those of doctors in other specialties (n = 3,514). Main outcome measures and results The respondents were asked about their current intention to undertake a doctoral degree. Factors associated with this were analysed. Only 7.3% of GPs had completed a doctoral degree. The corresponding figure in other specialties was 32.3% (p <0.001). In general practice the current intention to undertake a doctoral degree had only slightly increased over ten years. Most GPs had also decided not to undertake a doctorate. The main factors associated with the current intention to complete a doctoral degree were interest in attaining a senior position (OR 3.43, 95% CI 2.25-5.24), a position in a university hospital district (OR 2.89, 95% CI 1.69-4.94) or other sector than primary care (OR 1.87, 95% CI 1.18-2.96), one's father being a doctor (OR 2.01, 95% CI 1.09-3.72) and male gender (OR 1.63, 95% CI 1.05-2.54). Conclusion Research work in primary health care has been quite sparse. In general practice there is a need to increase teaching and guidance in research work.Peer reviewe

Representation transfer for differentially private drug sensitivity prediction

Motivation Human genomic datasets often contain sensitive information that limits use and sharing of the data. In particular, simple anonymization strategies fail to provide sufficient level of protection for genomic data, because the data are inherently identifiable. Differentially private machine learning can help by guaranteeing that the published results do not leak too much information about any individual data point. Recent research has reached promising results on differentially private drug sensitivity prediction using gene expression data. Differentially private learning with genomic data is challenging because it is more difficult to guarantee privacy in high dimensions. Dimensionality reduction can help, but if the dimension reduction mapping is learned from the data, then it needs to be differentially private too, which can carry a significant privacy cost. Furthermore, the selection of any hyperparameters (such as the target dimensionality) needs to also avoid leaking private information. Results We study an approach that uses a large public dataset of similar type to learn a compact representation for differentially private learning. We compare three representation learning methods: variational autoencoders, principal component analysis and random projection. We solve two machine learning tasks on gene expression of cancer cell lines: cancer type classification, and drug sensitivity prediction. The experiments demonstrate significant benefit from all representation learning methods with variational autoencoders providing the most accurate predictions most often. Our results significantly improve over previous state-of-the-art in accuracy of differentially private drug sensitivity prediction. Availability and implementation Code used in the experiments is available at https://github.com/DPBayes/dp-representation-transfer.Peer reviewe

Postitse vai sähköisesti? Näkemyksiä tiedonkeruumenetelmän valintaan Lääkäri 2008 –tutkimuksen pohjalta

Tässä artikkelissa pohditaan yhtäältä sähköisen tiedonkeruun, toisaalta paperisen ja sähköisen yhdistelmänä toteutetun tiedonkeruun mahdollisuuksia, haasteita ja ongelmia Lääkäri 2008 -tutkimuksen kokemusten valossa. Lääkäri 2008 -tutkimuksen tiedonkeruuta arvioidaan suhteessa yleisesti kyselytutkimuksessa havaittuihin virhelähteisiin, joita ovat kattavuusongelma, otosharha, vastauskato ja mittausvirhe. Artikkelin tavoitteena on auttaa muita tutkijoita ja tutkimusryhmiä tutkimusasetelman suunnittelussa ja oikean tiedonkeruumenetelmän valinnassa

What predicts doctors’ satisfaction with their chosen medical specialty? A Finnish national study

Background In Finland the number of medical specialists varies between specialties and regions. More regulation of the post-graduate medical training is planned. Therefore, it is important to clarify what predicts doctors’ satisfaction with their chosen specialty. Methods A random sample contained 50 % of all Finnish doctors under 70 years of age. The respose rate was 50.5 %. Working-age specialists were asked to value their motives when choosing a specialty. They were also asked if they would choose the same specialty again. The odds ratios for not choosing the same specialty again were tested. Results Diversity of work was the most important motive (74 % of respondents). Seventeen percent of GPs would not choose the same specialty again, compared to 2 % of ophthalmologists and 4 % of pediatricians. A major role of Diversity of work and Prestigious field correlated with satisfaction whereas Chance with dissatisfaction with the specialty. Discussion Motives and issues related to the work and training best correlate with satisfaction with the specialty. Conclusions When the numbers of Finnish postgraduate medical training posts become regulated, a renewed focus should be given to finding the most suitable speciality for each doctor. Information about employment and career advice should play an important role in this.BioMed Central open acces

New national and regional biological records for Finland 7. Contributions to Bryophyta and Marchantiophyta

Three species of mosses (Bryophyta: Philonotis yezoana, Protobryum bryoides, Rhynchostegium murale) and one of liverworts (Marchantiophyta: Moerckia flotoviana) are presented new for Finland. Timmia megapolitana, previously thought to be regionally extinct, is reported to being found again. New records in biogeographical provinces for 82 species of mosses and 34 species of liverworts are listed. Finally, 8 occurrences in provinces are removed due to misidentifications or missing specimens

Lääkäri 2018 : Uusinta tutkimustietoa lääkäreistä ja erikoislääkärikoulutuksesta

VertaisarvioituLähtökohdat Lääkäri 2018 -tutkimus kartoittaa suomalaisten lääkärien koulutusta, arvoja, ammatti-identiteettiä ja urasuunnitelmia. Tässä artikkelissa keskitymme erikoistumiskoulutuksen kysymyksiin ja kuvaamme tutkimusaineiston. Menetelmät Perusjoukon muodostivat alle 70-vuotiaat Suomessa asuvat laillistetut lääkärit, jotka olivat antaneet luvan henkilötietojen luovuttamiselle (n = 23 131). Otokseen valittiin Suomen Lääkäriliiton rekisteristä parillisina päivinä syntyneet lääkärit (n = 11 336). Kyselytutkimuksen vastaukset kerättiin sähköisellä ja paperilomakkeella. Vastausosuus oli 46 %. Tulokset Tärkeimmät erikoisalan valintaan vaikuttaneet tekijät olivat omat taidot ja persoonallisuus sekä alan monipuolisuus. Mahdollisuudella tutkimustyöhön tai yksityissektorilla toimimiseen ei ollut merkittävää vaikutusta. Vastanneista 72 % oli melko tai erittäin tyytyväisiä erikoislääkärikoulutukseensa. Päätelmät Aineisto antaa kattavan kuvan lääkärien taustatiedoista, näkemyksistä ja lääkärikoulutuksen kehitystarpeista vuonna 2018. Erikoisalavalintoihin vaikuttavat tekijät ovat yksilöllisiä, ja lääkärit ovat yleisesti tyytyväisiä valintaansa.Peer reviewe

Lääkäri 2018 : uusinta tutkimustietoa lääkäreistä ja erikoislääkärikoulutuksesta

Lähtökohdat Lääkäri 2018 -tutkimus kartoittaa suomalaisten lääkärien koulutusta, arvoja, ammatti-identiteettiä ja urasuunnitelmia. Tässä artikkelissa keskitymme erikoistumiskoulutuksen kysymyksiin ja kuvaamme tutkimusaineiston.Menetelmät Perusjoukon muodostivat alle 70-vuotiaat Suomessa asuvat laillistetut lääkärit, jotka olivat antaneet luvan henkilötietojen luovuttamiselle (n = 23 131). Otokseen valittiin Suomen Lääkäriliiton rekisteristä parillisina päivinä syntyneet lääkärit (n = 11 336). Kyselytutkimuksen vastaukset kerättiin sähköisellä ja paperilomakkeella. Vastausosuus oli 46 %.Tulokset Tärkeimmät erikoisalan valintaan vaikuttaneet tekijät olivat omat taidot ja persoonallisuus sekä alan monipuolisuus. Mahdollisuudella tutkimustyöhön tai yksityissektorilla toimimiseen ei ollut merkittävää vaikutusta. Vastanneista 72 % oli melko tai erittäin tyytyväisiä erikoislääkärikoulutukseensa.Päätelmät Aineisto antaa kattavan kuvan lääkärien taustatiedoista, näkemyksistä ja lääkärikoulutuksen kehitystarpeista vuonna 2018. Erikoisalavalintoihin vaikuttavat tekijät ovat yksilöllisiä, ja lääkärit ovat yleisesti tyytyväisiä valintaansa