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COVID-19 pandemien forandrede kontoret. De tvungne hjemsendelser indebar for mange et brat skifte fra at tilbringe arbejdsdagen på kontoret til i stedet at tilbringe den i stuen, køkkenet, sommerhuset, børneværelset eller ligefrem i et andet land. Selvom restriktioner og nedlukninger foreløbigt er slut i Danmark, så fortsætter hjemmearbejdet – til en vis grad. Flere arbejdspladser er blevet hybridarbejdspladser, hvilket indebærer, at medarbejderne arbejder både på kontoret og fra distancen, fx fra hjemmet. Det kan være ved, at medarbejderne arbejder nogle dage om ugen på kontoret og nogle dage fra distancen, eller det kan være, at nogle arbejder udelukkende på kontoret, mens andre arbejder udelukkende fra distancen (Yang et al., 2021). Den hybride arbejdsplads er et globalt fænomen (OECD, 2021), og internationale virksomheder som Twitter, Facebook og Siemens er overgået til at være hybride arbejdspladser (Heater, 2020; Choudhury et al., 2021). I Danmark har blandt andet Danske Bank og Deloitte (DK) indført permanente hybridarbejdsordninger og fleksible kontorer (Mandrup, 2020; Matzon, 2021). Tjenester som eksempelvis Zoom, Teams, Google Hangout, Miro og Slack er essentielle digitale infrastrukturer på mange hybridarbejdspladser, fordi de muliggør virtuelt samarbejde. Brugen af dem efterlader digitale spor, og dermed er mængden af digitale data på arbejdspladserne mangedoblet. En tendens, der er parallel til den generelle udvikling i samfundet, hvor mere og mere data indsamles, opbevares og analyseres. Vi argumenterer for, at fremtidige undersøgelser af arbejdslivet, særligt hybridarbejdslivet, med fordel kan bruge de digitale data som empirisk grundlag. For at kunne bruge denne data bedst muligt foreslår vi, at forskere trækker på forskningsfeltet Social Data Science, der integrerer de samfundsvidenskabelige spørgsmål, metoder og emnefelter med Data Sciences metoder til at behandle og analysere digitale data.

In the past decades, behavioral economics has credibly identified numerous decision-making biases leading people to make choices they would not have made if better informed about the long-term consequences of their actions. This has given rise to a new reason for government interventions: internalities. In contrast to traditional reasons for government intervention, such as redistribution and externalities, overcoming internalities often involves the use of paternalistic policies. We investigate theoretically and empirically the formation of attitudes toward paternalistic policies. Theoretically, we focus on the role of self-interest and distinguish between self-interest as construed for the rational decision-maker, self-interest when self-control problems are present, and self-interest when procedural or expressive elements, such as autonomy, matter. Empirically, we employ two novel data sets: a Danish survey on political opinion combined with administrative data on actual behavior and a large-scale cross-country survey to analyze attitudes toward paternalistic policies in the health and financial domains. We show that targets of paternalism are more opposed to paternalism than non-targets both in Denmark and across nine Western democracies and rely on our theoretical priors to explore mechanisms that can explain these attitudes.

National audience; While social pressure is widely believed to influence voters, evidence that information passed between social ties affects beliefs, policy preferences, and voting behavior is limited. We investigate whether information about unemployment shocks diffuses through networks of strong and mostly weak social ties and influences voters in Denmark. We link surveys with population-level administrative data that log unemployment shocks afflicting respondents’ familial, vocational, and educational networks. Our results show that the share of second-degree social ties—individuals that voters learn about indirectly—that became unemployed within the last year increases a voter’s perception of national unemployment, self-assessed risk of becoming unemployed, support for unemployment insurance, and voting for left-wing political parties. Voters’ beliefs about national aggregates respond to all shocks similarly, whereas subjective perceptions and preferences respond primarily to unemployment shocks afflicting second-degree ties in similar vocations. This suggests that information diffusion through social ties principally affects political preferences via egotropic—rather than sociotropic—motives.

Greenland’s residents and Ice Sheet are both exposed to pronounced Arctic warming. Although Greenland is a hub for climate science, the climate perceptions of Greenland’s predominantly Indigenous population remained unstudied through the past decade of multi-national climate opinion polls. Conducting two original nationally representative surveys, here we show that Greenlanders are more likely than residents of top oil-producing Arctic countries to perceive that climate change is happening, and about twice as likely to have personally experienced its effects. However, half are unaware that climate change is human-caused, and those who are most affected appear to be least aware. An Inuit cultural dimension, indicated by the intertwined social ecological factors of Indigenous identity, subsistence occupation, village community scale and no post-elementary education, proves to be the main positive predictor of climate change experience but also the strongest negative predictor of awareness of human-caused climate change. Despite Greenland’s centrality to climate research, we uncover a widespread gap between the scientific consensus and coastal Kalaallit views of climate change, particularly among the country’s youth, fishers, and hunters. This science-society gulf has immediate and prospective implications for local climate adaptation, climate science communication and knowledge exchange between generations, institutions, and communities.

Topic models (TMs) have become the de facto standard for automated content analysis in the social sciences. Some problematic aspects of the models, however, have been recently identified. These mainly concern the high variability of solutions that is the result of both preprocessing and non-deterministic inference in high-dimensional and very large solution spaces. Whether current model selection and validation practices are sufficient to ensure precise and unbiased measurement has been the subject of debate. This paper argues that the prevalent practices of model selection and validation for ensuring unbiased measurement are indeed insufficient. This paper focus is on the use of summarization techniques during labeling, indirect validation techniques, and the employment of heuristics for model selection. Our results document non-trivial biases and show that current model validation techniques lead to arbitrary research outcomes. The study concludes by providing recommendations on ways to validate work based on topic models.

Topic models (TMs) have become the de facto standard for automated content analysis in the social sciences. Some problematic aspects of the models, however, have been recently identified. These mainly concern the high variability of solutions that is the result of both preprocessing and non-deterministic inference in high-dimensional and very large solution spaces. Whether current model selection and validation practices are sufficient to ensure precise and unbiased measurement has been the subject of debate. This paper argues that the prevalent practices of model selection and validation for ensuring unbiased measurement are indeed insufficient. This paper focus is on the use of summarization techniques during labeling, indirect validation techniques, and the employment of heuristics for model selection. Our results document non-trivial biases and show that current model validation techniques lead to arbitrary research outcomes. The study concludes by providing recommendations on ways to validate work based on topic models.

During their period of summer dormancy, Australian Bogong mothsAgrotis infusaundertake seemingly random evening flights, filling the air with densities in the dozens per cubic metre. The purpose of these flights is unknown, but they may serve an important role in Bogong moth navigation, which remarkably enables them to return to the same exact summer sites— generation after generation—after migrating around 1000 km, and with no opportunity to learn their route or destination from prior generations. The recent development of the camera-based insect monitoring method, Camfi, enables quantitative observations of Bogong moth behaviour at an unprecedented scale. To gain a better understanding of the summer evening flights of Bogong moths, we have extended Camfi to facilitate automated video tracking of flying insects, taking the already-high throughput of the method to a new level. We used this new method to record the evening flight behaviour of Bogong moths in two elevational transects below the summit of Mt. Kosciuszko, NSW, on a single night in February 2021, and found that these flights were not random, but were systematically oriented in directions relative to the azimuth of the summit of the mountain. These results stimulate interesting and plausible hypotheses relating to previously unexplained summer evening flight behaviour of Bogong moths, and the mechanisms of their long-distance navigation.

The Bogong moth Agrotis infusa is well known for its remarkable annual round-trip migration from its breeding grounds across eastern Australia to its aestivation sites in the Australian Alps, to which it provides an important annual influx of nutrients. Over recent years, we have benefited from a growing understanding of the navigational abilities of the Bogong moth. Meanwhile, the population of Bogong moths has been shrinking. Recently, the ecologically and culturally important Bogong moth was listed as endangered by the IUCN Red List, and the establishment of a program for long-term monitoring of its population has been identified as critical for its conservation. Here, we present the results of two years of monitoring of the Bogong moth population in the Australian Alps using a recently developed method for automated monitoring of flying insects, named Camfi. We found that the evening flights of Bogong moths occur throughout summer, and are modulated by daily weather factors. We present a simple heuristic model of the arrival to and departure from aestivation sites by Bogong moths, and confirm results obtained from fox-scat surveys which found that aestivating Bogong moths occupy higher elevations as the summer progresses. We also present the first recorded observations of the impact of bushfire smoke on aestivating Bogong moths. We observed a dramatic reduction in the size of a cluster of aestivating Bogong moths during the fire, and evidence of a large departure from the fire-affected area the day after the fire. Our results highlight the challenges of monitoring Bogong moths in the wild, and support the continued use of automated camera-based methods for that purpose.

Refereed/Peer-reviewed The Bogong moth Agrotis infusa is well known for its remarkable long-distance migration – a return journey from the plains of southeast Australia to the Australian Alps – as well as for its cultural significance for Indigenous Australians. Each spring, as many as four billion moths are estimated to arrive in the Australian Alps to aestivate in cool mountain caves and in boulder fields, bringing with them a massive annual influx of energy and nutrients critical for the health of the alpine ecosystem. However, a massive decline in moths present at their aestivation sites has occurred over the past 3 years, with only a few individuals present where hundreds of thousands could earlier be found. In order to understand the possible sources of decline, we analysed historical records of Bogong moth numbers at aestivation sites in the Australian Alps, including observations on Mt. Gingera (NSW) in the early 1950s, observations from 1980 onwards in the Snowy Mountains (NSW) and an almost-unbroken series of observations each summer over the past 53 years in three caves at different elevations on Mt. Buffalo (Victoria). This analysis shows that moth numbers were probably steady from 1951 until about 1980, fluctuated and slowly fell from then until 2016 and dramatically crashed in 2017. In the Murray–Darling Basin, the main winter breeding ground of Bogong moths, changes in farming practices, such as increasing land clearing for crops (which has removed around a quarter of a billion moths annually from the mountains compared to pre-European levels), has probably driven some of the decline in Bogong moth numbers observed from 1980 to 2016. The impact of insecticide remains unclear and is in urgent need of further study. Even though we found little evidence that increasing global temperatures per se are responsible for the Bogong moth decline, the Australian climate has nonetheless become drier and warmer over past decades, possibly hampering the survival of immature stages in the breeding areas and confining adult aestivation to gradually higher elevations. The crash in moth numbers from 2017 is most likely due to the recent severe drought in the moth's breeding grounds.

The High-Level Expert Group on facilitating the use of new data sources for official statistics has been created in the context of the data and digital strategy of the European Commission (EC). The task of the Expert Group is to provide recommendations aimed at enhancing data sharing between businesses and government (B2G) for the purpose of producing official statistics (B2G4S). The Expert Group consists of high-level experts with various backgrounds that are particularly relevant to B2G4S. Businesses generate and use data primarily for business-related purposes. The motivation for B2G4S stems from the high societal value that such privately held data can potentially generate when transformed into reliable, relevant and timely official statistics that are made available to everybody, for free. Transforming data into statistical information requires cooperation between private data holders and statistical authorities. On a voluntary basis there have been many collaborative efforts by businesses and statistical authorities to produce statistics based on privately held data, but for various reasons the use of such data for official statistics is still far below the level required to provide society with the high-quality and timely official statistics it needs in the increasingly data-driven world.

The ability to measure flying insect activity and abundance is important for ecologists, conservationists and agronomists alike. However, existing methods are laborious and produce data with low temporal resolution (e.g. trapping and direct observation), or are expensive, technically complex, and require vehicle access to field sites (e.g. radar and lidar entomology).We propose a method called “camfi” for long-term non-invasive monitoring of the activity and abundance of low-flying insects using images obtained from inexpensive wildlife cameras, which retail for under USD$100 and are simple to operate. We show that in certain circumstances, this method facilitates measurement of wingbeat frequency, a diagnostic parameter for species identification. To increase usefulness of our method for very large monitoring programs, we have developed and implemented a tool for automatic detection and annotation of flying insect targets based on the popular Mask R-CNN framework. This tool can be trained to detect and annotate insects in a few hours, taking advantage of transfer learning.We demonstrate the utility of the method by measuring activity levels and wingbeat frequencies in Australian Bogong moths Agrotis infusa in the Snowy Mountains of New South Wales, and find that these moths have log-normally distributed wingbeat frequencies (mean = 49.4 Hz, std = 5.25 Hz), undertake dusk flights in large numbers, and that the intensity of their dusk flights is modulated by daily weather factors. Validation of our tool for automatic image annotation gives baseline performance metrics for comparisons with future annotation models. The tool performs well on our test set, and produces annotations which can be easily modified by hand if required. Training completed in less than 2 h on a single machine, and inference took on average 1.15 s per image on a laptop.Our method will prove invaluable for ongoing efforts to understand the behaviour and ecology of the iconic Bogong moth, and can easily be adapted to other flying insects. The method is particularly suited to studies on low-flying insects in remote areas, and is suitable for very large-scale monitoring programs, or programs with relatively low budgets.

It has been suggested that the use of etanercept for treatment of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) might provide improved mortality benefit and decreased skin healing times. This retrospective study compared the use of single-dose subcutaneous etanercept to intravenous immunoglobulin (IVIG) and supportive care alone. Thirteen patients were treated with a single dose (50 mg) of subcutaneous etanercept. Results of this study support the use of etanercept as a potentially beneficial agent in the treatment of SJS/TEN.

In this article, we show that it is crucial to distinguish between liquid and illiquid wealth to understand how voters form preferences toward social insurance. Many households are financially fragile despite having high incomes and wealth, because they hold little liquid savings. We hypothesize, and show empirically, that this implies that a substantial group of voters show strong support for social insurance policies despite being wealthy and having high incomes, because of their limited ability to self-insure through own savings in case of an income shock. Our empirical analysis is based on a novel dataset from Denmark, which combines administrative data with high-quality measures of individual financial assets and survey measures of political preferences. Using data for other countries from the European Social Survey, we find evidence that our results hold more generally and are not specific to the Danish context.