Fake news and copyright

As is known, new technologies have profoundly changed the way content is produced, shared and disseminated. One of the most recent (and worrying) changes is the phenomenon of ‘fake news’, especially since disinformation and intentional misrepresentation of real information have started to affect individual decision-making in the political sphere. It is a worrying phenomenon because the dissemination of fake news can challenge democratic values and undermine national security. Against this background, can copyright play a role in the fight against fake news? And what is the relationship between such news and copyright in the first place? Fake news in theory falls within copyright subject matter and may often meet the requirements for protection. The paper analyses three recent examples of fake news which have been widely disseminated online – and makes the point that copyright may subsist in such news. Yet, despite such content being potentially capable of attracting protection, we propose to remove any copyright which may arise on grounds of public interest. Indeed, when a work is protected by copyright, right holders have an incentive to exploit it, as the monopoly granted to them increases the ability to extract profits out of the work, for example via licensing. This may contribute to encouraging creators of fake news to spread such content across multiple channels to reach wide audiences. Excluding copyright could therefore help make fake news less appealing. A short reference will also be made to copyright defences which may be relied on by entities and individuals who check news’ accuracy (fact-checkers) – that is, the fair use doctrine under US law and several exceptions under EU (and UK) law, namely transient use, text and data mining, criticism and review and public security. * All authors contributed equally to this manuscript and are listed alphabetically.

The effect of individuals’ analytical orientation and capabilities on decision quality and regret

Decision makers are exposed to an increasing amount of information. Algorithms can help people make better data-driven decisions. Previous research has focused on both companies’ orientation towards analytics use and the required skills of individual decision makers. However, each individual can make either analytically based or intuitive decisions. We investigated the characteristics that influence the likelihood of making analytical decisions, focusing on both analytical orientation and capabilities of individuals. We conducted a survey using 462 business students as proxies for decision makers and used partial least squares path modeling to show that analytical capabilities and analytical orientation influence each other and affect analytical decision-making, thereby impacting decision quality and decision regret. Our findings suggest that when implementing business analytics solutions, companies should focus on the development not only of technological capabilities and individuals’ skills but also of individuals’ analytical orientation.

Industrial robot selection using a multiple criteria group decision making method with individual preferences

This paper proposes a multiple criteria group decision making with individual preferences (MCGDM-IP) to address the robot selection problem (RSP). Four objective criteria elicitation approaches, namely, Shannon entropy approach, CRITIC approach, distance-based approach, and ideal-point approach, are proposed to indicate individual decision makers. A preliminary group decision matrix is therefore formulated. Both preferential differences representing the preference degrees among different robots, and preferential priorities representing the favorite ranking of robots for each individual decision maker, are analyzed to propose a revised group decision matrix. A satisfaction index is developed to manifest the merits of the proposed MCGDM-IP. An illustrative example using the data drawn from previous literature is conducted to indicate the effectiveness and validity of MCGDM-IP. The results demonstrate that the MCGDM-IP could generate a more satisfactory scheme to evaluate and select industrial robots, with an improvement of group satisfactory level as 2.12%.

In Search of Autonomy: Dancing With Rules

Purpose: Autonomy in organisations cannot exist without rules nor relationships. Yet, previous research tends to elicit understandings of autonomy as freedom from external constraints to enact free individual will. And there are numerous positive effects related to autonomy at work. But research has not kept pace with modern-day organisations that are highly flexible and dynamic. Current understandings of autonomy are static. Autonomy is mainly regarded as something individuals possess, more or less constricted by rules. Our purpose is to contribute a more flexible and practice-oriented concept of autonomy to answer the research question: How is autonomy developed and practiced in relation to formal rules in high-risk organisations?Design: To investigate autonomy as a dynamic and flexible concept, we draw on two case studies comprised of a total of 52 interviews and more than 10 h of observation. The cases include a factory and a hospital unit.Findings: We suggest, based on the data, that autonomy is a relational phenomenon. We suggest four different autonomy-rule dynamics: Passive, loyal, self-promoting, and co-generative learning.Research Implications: Regarding autonomy as relational rather than individual contributes to our understanding of organisations as always in the making. In this, we emphasise the interactive element of autonomy.Practical Implications: Practitioners and managers may use our suggestions to work with autonomy in a different way, spurring creativity and improvisation by constructively using rules.Originality: Little research has paid attention to the concept of autonomy (despite its importance), and arguably, a trend in the available research concerns a commodification of the phenomenon, primarily aligning autonomy with (degrees of) negative freedom and individual decision making. We unpack the concept with attention to interaction – what we have called dancing with rules.

Cranial and Spinal Metastasis of a Nonfunctioning Pituitary Adenoma: Report of a Case

Pituitary carcinoma is a rare disease with surgical, radiotherapeutic, and chemotherapeutic treatment options. We present the case of a female patient diagnosed with a nonfunctioning pituitary adenoma who underwent several surgical procedures, radiations, and chemotherapeutic treatments with various substances. Sixteen years after the first diagnosis, a cranial and spinal metastatic spread of the tumor occurred. We opted for an individual therapy based on anecdotal evidence. Unfortunately, the recommended off-label treatment with a somatostatin analog substance was never given due to bureaucratic delays. This case report is about the challenging aspects of individual decision-making in rare neurosurgical diseases.

Collectivized Discretion: Seeking Explanations for Decreased Asylum Recognition Rates in Finland After Europe's 2015 “Refugee Crisis”

In 2015, during the so-called “refugee crisis” in Europe, Finland was among the European countries receiving exceptionally large numbers of asylum applications. As the volume of asylum applications surged, however, the percentage of positive asylum decisions in Finland declined substantially. In this article, we explore reasons for this dramatic drop in recognitions rates and examine Finnish immigration control authorities’ use of discretion in asylum credibility assessment. Our approach is unique in its application of mixed methods to examine asylum decisions in pre- and post-crisis situations. We found that asylum caseworkers’ inconsistent assessment of similar facts and lack of faith in the veracity of applicants’ claims were essential to the mass denial of young Iraqi asylum applicants in Finland. This finding is important because it illustrates how asylum officers are able to “shift the border,” or generate a shift in asylum decision-making on a grand scale, without meaningful changes in law. Asylum officers, we show, are able to bring about such a shift via what we call collectivized discretion, or large-scale use of discretion, in asylum status determinations to control migration. Prior research on discretion in asylum decision-making highlights the individual decision-maker. This article expands discretion research by offering new insights on large-scale, collective discretionary shifts in the application of asylum law. We conclude that it is crucial that asylum status determinations be anchored in the individual assessment of each applicant's case, as collectivized discretion can lead to arbitrary results in the application of asylum law, potentially forcing those in need of refugee protection to face deportation.

Social cohesion at the outset of COVID-19 predicts later vaccination intentions

Vaccination intentions are widely regarded as individual decision, resting upon individuals’ attitudes and beliefs about the disease and their own health. In this research, we provide evidence that group factors, and more precisely, social cohesion — a multidimensional concept that encompasses one’s sense of connectedness to, and interrelations within, a group — can help us understand COVID-19 vaccination intentions. Using a representative sample of 3026 Australians, we first found evidence for the multidimensional structure of social cohesion, as a concept that includes positive social relations, social identification, and trust in government. Second, social cohesion assessed early in the COVID-19 pandemic predicted greater vaccination intention and lower perceived risk of vaccination four months later, after controlling for a series of demographic (i.e., sex, age, income) and health-related factors (i.e., subjective health; perceived risk; having been diagnosed with COVID-19). These results suggest that investments in social cohesion could have substantial and unexpected downstream benefits.

Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

Hurricane Irma, in 2017, made an unusual landfall in South Florida and the unpredictability of the hurricane’s path challenged the evacuation process seriously and left many evacuees clueless. It was likely to hit Southeast Florida but suddenly shifted its path to the west coast of the peninsula, where the evacuation process had to change immediately without any time for individual decision-making. As such, this study aimed to develop a methodology to integrate evacuation and storm surge modeling with a case study analysis of Irma hitting Southeast Florida. For this purpose, a coupled storm surge and wave finite element model (ADCIRC+SWAN) was used to determine the inundation zones and roadways with higher inundation risk in Broward, Miami-Dade, and Palm Beach counties in Southeast Florida. This was fed into the evacuation modeling to estimate the regional clearance times and shelter availability in the selected counties. Findings show that it takes approximately three days to safely evacuate the populations in the study area. Modeling such integrated simulations before the hurricane hit the state could provide the information people in hurricane-prone areas need to decide to evacuate or not before the mandatory evacuation order is given.