What Do We Work For? An Anatomy of Pre- and Post-Tax Earnings Growth

Promotions and cross-firm mobility provide substantial gains in earnings – a well established finding based on gross income data. Yet, what matters for incentives is how much an individual can consume or save after taxation. We show that net and gross income growth patterns may differ substantially when a progressive tax system allows for deduction opportunities. Exploiting unique matched employer-employee data with information on tax payments and employee mobility, we find that gross income gains from promotions and cross-firm mobility do not translate into significantly higher net income growth, because employees adjust their tax-shielded consumption and savings (in particular, deductible private pension contributions and mortgage-financed housing) to maintain constant net income growth.earnings growth, promotions, mobility, taxable income, dynamic panel data models, matched employer-employee data

Welfare within planetary limits: deep transformation requires holistic approaches

In January 2023, Anders Rhiger Hansen visited Lund University to talk to Max Koch about sustainable welfare, human needs, social inequality and a little bit about Bourdieu. The message from Max was clear: politicians need to drop the idea of green growth and instead define a safe and just operating space to determine what can be done within this space. His sociological approach combines Marxian and Bourdieusean traditions, and he recommends that the Consumption and Society community investigates consumption in combination with processes of production, for example by engaging with critical political economy approaches such as the French regulation school or the Frankfurt School. According to Koch, the survival of the planet requires holistic approaches that would transform society and its exchanges with nature, based on principles of degrowth and on a scale that we have not yet seen

Sexual Health and Sexually Transmitted Infections in the North American Arctic

STI rates reported for the Arctic are much higher than those reported for their southern counterparts

Ten years of tuberculosis intervention in Greenland – has it prevented cases of childhood tuberculosis?

Background: The incidence of tuberculosis (TB) disease in Greenland doubled in the 1990s. To combat the increase, national TB interventions were initiated in 2000 and strengthened in 2007. Objective: To determine whether the effect of interventions could be detected, we estimated the TB disease risk among children≤15 years before and after interventions were implemented. Design: For a study cohort, we recruited all children ≤15 years of age included in the Greenlandic Civil Registration System (CRS) from 1990 to 2010. The CRS identifier was used to link cohort participants with TB cases identified based on the Greenlandic National TB registry. Bacille Calmette Guerin (BCG) vaccination status was identified through year of birth, as BCG was offered to newborns born either before 1991 or after 1996. Years with interventions were defined as 2000–2006 (primary interventions) and 2007–2010 (intensified interventions). Risk of TB was estimated using Poisson regression. Results: The study included 35,858 children, of whom 209 had TB disease. The TB disease incidence decreased after interventions were implemented (2007–2010: IRR [incidence rate ratios] 0.62, 95% CI: 0.39–0.95, p=0.03, compared with the 1995–1999 period). The TB disease risk was inversely associated with BCG vaccination (IRR: 0.54, 95% CI: 0.41–0.72, p<0.001). Conclusions: Years with national TB interventions in Greenland, including neonate BCG vaccination, are associated with a lower TB disease incidence among children ≤15 years of age

Maximizing citizen scientists’ contribution to automated species recognition

publishedVersio

Population-based Survey of Invasive Bacterial Diseases, Greenland, 1995–2004

Invasive bacterial disease occurs frequently among native populations in the Arctic. Although a variety of bacteria are involved in invasive bacterial disease in Greenland, Streptococcus pneumoniae, Escherichia coli, Staphylococcus aureus, and other staphylococci are responsible for most cases (69%); incidence varies according to region and ethnicity

Accounting for Misclassification in Multispecies Distribution Models

1. Species identification errors may have severe implications for the inference of species distributions. Accounting for misclassification in species distributions is an important topic of biodiversity research. With an increasing amount of biodiversity that comes from Citizen Science projects, where identification is not verified by preserved specimens, this issue is becoming more important. This has often been dealt with by accounting for false positives in species distribution models. However, the problem should account for misclassifications in general. 2. Here we present a flexible framework that accounts for misclassification in the distribution models and provides estimates of uncertainty around these estimates. The model was applied to data on viceroy, queen and monarch butterflies in the United States. The data were obtained from the iNaturalist database in the period 2019 to 2020. 3. Simulations and analysis of butterfly data showed that the proposed model was able to correct the reported abundance distribution for misclassification and also predict the true state for misclassified state

Human Dorset Remains from Igloolik, Canada

Skeletal remains of four Dorset Palaeo-Eskimo individuals were found at Alarnerk (NhHd-1), Melville Peninsula, in 1954 by the joint Danish National Museum-University of Pennsylvania Expedition, which was excavating Dorset and pre-Dorset sites. These remains included one complete mandible, two fragmentary mandibles, and a cranial fragment. One of the mandibular fragments, found in a grave, was from a child approximately nine months old. The other remains were found in middens at the site. These remains add to the otherwise very sparse Dorset human material. Analysis of the dental morphology, as well as morphometric analysis of the complete mandible, shows Eskimoid characters and resemblance with later period Greenlandic human skeletal remains.En 1954, à Alarnerk (NhHd-1) dans la péninsule de Melville, l'expédition menée conjointement par le Musée national du Danemark et l'université de Pennsylvanie pour effectuer des fouilles sur des sites de culture dorset et pré-dorset, a mis au jour des restes humains appartenant à quatre individus du paléo-esquimau du Dorset. Ces restes comprenaient une mâchoire inférieure complète, deux mâchoires inférieures partielles et un fragment de crâne. L'un des fragments mandibulaires, trouvé dans une sépulture, appartenait à un enfant âgé d'environ neuf mois. Les autres restes ont été découverts dans des tertres localisés sur le site. Ces restes viennent s'ajouter aux très rares éléments humains du Dorset déjà mis au jour. L'analyse de la morphologie dentaire du mandibule complet, ainsi que son analyse morphométrique, révèle des caractères esquimoïdes et une ressemblance avec des restes de squelettes humains groenlandais datant d'une période postérieure

Recognizability bias in citizen science photographs

Citizen science and automated collection methods increasinglydepend on image recognition to provide the amountsof observational data research and management needs.Recognition models, meanwhile, also require large amounts ofdata from these sources, creating a feedback loop between themethods and tools. Species that are harder to recognize, bothfor humans and machine learning algorithms, are likely to beunder-reported, and thus be less prevalent in the trainingdata. As a result, the feedback loop may hamper trainingmostly for species that already pose the greatest challenge. Inthis study, we trained recognition models for various taxa, andfound evidence for a‘recognizability bias’, where species thatare more readily identified by humans and recognitionmodels alike are more prevalent in the available image data.This pattern is present across multiple taxa, and does notappear to relate to differences in picture quality, biologicaltraits or data collection metrics other than recognizability. Thishas implications for the expected performance of futuremodels trained with more data, including such challenging species. citizen science, image recognition, machinelearning, recognizability, artificial intelligence/environmental science/ecology, Ecology, conservation and global change biologypublishedVersio