'NetzWerkstatt': Pilotprojekt zur internetbasierten Beratung und Begleitung qualitativer Forschungsarbeiten in den Sozialwissenschaften

"Mit dem Internet sind neue Untersuchungsfelder und Methodenentwicklungen für die Sozialwissenschaften entstanden. Zugleich hat das Internet die (sozial-)wissenschaftliche Praxis selbst verändert. So wurden spezifische Mediennutzungen (insbesondere von E-Mails) für die wissenschaftliche Kommunikation bereits früh genutzt, weitere Tools sind einsetzbar. Das Projekt NetzWerkstatt ( http://www.methodenbegleitung.de/ ), über das hier berichtet werden soll, schließt an die besonderen Potenziale des Internet für eine integrierte Begleitung von Forschungsarbeiten an. Basis der NetzWerkstatt ist ein - ursprünglich für Offline-Gruppen entwickeltes - Konzept, das sukzessive für die Online-Beratung und -Begleitung qualitative forschender Sozialwissenschaftler(innen) weiterentwickelt wurde. Hierzu kommen die Lernplattform Blackboard nutzend verschiedene Komponenten (u.a. eine Online-Bibliothek, Mailinglisten, Chats, Diskussionsforen) zum Einsatz, um standortunabhängig, unmittelbar und kontinuierlich dezentral arbeitende Wissenschaftler(innen) methodisch unterstützen zu können. Bisher werden in insgesamt vier Kleingruppen vor allem Nachwuchswissenschaftler(innen) während ihres gesamten Arbeitsprozesses begleitet. Eine konzeptuelle Ausweitung des Angebots für Einzelforscher(innen) und für Forschungsgruppen ist vorgesehen." (Autorenreferat

Rätt person på rätt plats

Title: The perfect candidate – the selection process in a global organization. Authors: Kariin Adolfsson and Simon Leetsaar In today's society, it becomes increasingly current with correct person on correct place in the working life. What requires knowledge about how to recruit in a professional manner and reliable ways. In many bigger organizations, there is today a human resources department that only works with recruitment of new employees. The purpose with our research is to describe personnel selection process in a big swedish organization, how they work throughout the entire process. The study is based on three qualitative interviews and observations of two focus group interviews. The qualitative interviews were held with the personnel manager, deputy personnel manager and the recruiting manager. Moreover, a summary was formulated of the documents that the organization had given us access to. The results from the interviews and observations has then been analyzed compared to theoretical concepts chosen for the study. The analysis of the result shows that the organisation follows a surely prepared procedure in the personnel selection process that reflects the theoretical concepts chosen for the study. Finally, suggestions is presented how the organisation can work furthermore in order to improve their work with recruitment

ChatGPT: En trussel mot vår mestringsevne?

Sammendrag Ifølge Aristoteles (2013) søker vi mennesker å virke på vårt beste, realisere vårt fulle potensiale og oppnå lykke. Mestring er en viktig del av denne prosessen. Når vi bruker vår intelligens til å mestre nye oppgaver, føler vi tilfredshet og personlig utvikling. Dagens samfunn preges i sterk grad av mestringens mester: kunstig intelligens (KI). KI er et fast innslag i den moderne hverdagen via for eksempel Facebook, Google, Netflix, Instagram, YouTube og Spotify. En rekke saker som tidligere ble løst av menneskelig intelligens, løses nå av menneskelignende intelligens. Ny blant KI-ene er ChatGPT, en avansert chatbot som kan prosessere gigantiske mengder med data. Det er mye som er bekymringsverdig med ChatGPT, men i dette debattinnlegget tar vi for oss bekymringen om at ChatGPT kan utgjøre en trussel mot vår mestringsevne. På bakgrunn av Aristoteles’ idé om å virke på det beste, vil vi spekulere i om overdreven ChatGPT-bruk kan ha negativ innvirkning på evnen til å oppnå genuin mestringsfølelse

A Markovian analysis of bacterial genome sequence constraints

The arrangement of nucleotides within a bacterial chromosome is influenced by numerous factors. The degeneracy of the third codon within each reading frame allows some flexibility of nucleotide selection; however, the third nucleotide in the triplet of each codon is at least partly determined by the preceding two. This is most evident in organisms with a strong G + C bias, as the degenerate codon must contribute disproportionately to maintaining that bias. Therefore, a correlation exists between the first two nucleotides and the third in all open reading frames. If the arrangement of nucleotides in a bacterial chromosome is represented as a Markov process, we would expect that the correlation would be completely captured by a second-order Markov model and an increase in the order of the model (e.g., third-, fourth-…order) would not capture any additional uncertainty in the process. In this manuscript, we present the results of a comprehensive study of the Markov property that exists in the DNA sequences of 906 bacterial chromosomes. All of the 906 bacterial chromosomes studied exhibit a statistically significant Markov property that extends beyond second-order, and therefore cannot be fully explained by codon usage. An unrooted tree containing all 906 bacterial chromosomes based on their transition probability matrices of third-order shares ∼25% similarity to a tree based on sequence homologies of 16S rRNA sequences. This congruence to the 16S rRNA tree is greater than for trees based on lower-order models (e.g., second-order), and higher-order models result in diminishing improvements in congruence. A nucleotide correlation most likely exists within every bacterial chromosome that extends past three nucleotides. This correlation places significant limits on the number of nucleotide sequences that can represent probable bacterial chromosomes. Transition matrix usage is largely conserved by taxa, indicating that this property is likely inherited, however some important exceptions exist that may indicate the convergent evolution of some bacteria

Unsupervised statistical clustering of environmental shotgun sequences

© 2009 Kislyuk et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2105/10/316DOI: 10.1186/1471-2105-10-316Background: The development of effective environmental shotgun sequence binning methods remains an ongoing challenge in algorithmic analysis of metagenomic data. While previous methods have focused primarily on supervised learning involving extrinsic data, a first-principles statistical model combined with a self-training fitting method has not yet been developed. Results: We derive an unsupervised, maximum-likelihood formalism for clustering short sequences by their taxonomic origin on the basis of their k-mer distributions. The formalism is implemented using a Markov Chain Monte Carlo approach in a k-mer feature space. We introduce a space transformation that reduces the dimensionality of the feature space and a genomic fragment divergence measure that strongly correlates with the method's performance. Pairwise analysis of over 1000 completely sequenced genomes reveals that the vast majority of genomes have sufficient genomic fragment divergence to be amenable for binning using the present formalism. Using a highperformance implementation, the binner is able to classify fragments as short as 400 nt with accuracy over 90% in simulations of low-complexity communities of 2 to 10 species, given sufficient genomic fragment divergence. The method is available as an open source package called LikelyBin. Conclusion: An unsupervised binning method based on statistical signatures of short environmental sequences is a viable stand-alone binning method for low complexity samples. For medium and high complexity samples, we discuss the possibility of combining the current method with other methods as part of an iterative process to enhance the resolving power of sorting reads into taxonomic and/or functional bins