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The Copyright Chapter of the EU’s Code of Practice for General-Purpose AI Models: A Commentary
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This article, written by the working group chairs responsible for the drafting of the Copyright Chapter of the EU’s Code of Practice for General-Purpose AI Models (GPAI CoP), briefly outlines the legal basis of the GPAI CoP and the process leading to its adoption before providing a commentary-style explanation of the Objectives, Recitals, the Commitment and the Measures of the Copyright Chapter. The article concludes with an assessment of the potential impact of the Copyright Chapter on the global regulatory landscape
Measuring entrepreneurial ecosystems across levels: a district approach
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Entrepreneurial ecosystem measures should combine archival civic and self-reported entrepreneur data. This combination helps to overcome the limitations of aggregated archival data that affect our collective capacity to derive actionable insights for research and policy. Previous measurement approaches lack consistency with entrepreneurial ecosystem theory because they do not capture data at a sufficiently local level or data about entrepreneurs’ values, beliefs, and attitudes. This paper proposes a new measurement approach for EE elements at the district level (NUTS-3), facilitating comparisons of local geographic EE properties and measuring relations between entrepreneurs, new ventures, and their ecosystems. Using confirmatory factor analysis, we combine self-reported and archival data to connect the micro and macro dimensions of the entrepreneurial ecosystem phenomenon. Analyzing survey data from 257 founders of innovative startups across 29 NUTS-3 districts in Baden-Württemberg, Germany, our findings support the “substitutability logic” among ten entrepreneurial ecosystem elements and uncover district-level geographic properties. Our study offers replication possibilities, recommendations for entrepreneurs’ actions, and policy monitoring. Plain English Summary: Policymakers appear to “bend over backwards” to facilitate entrepreneurs, new ventures, and their local ecosystems with various interventions—but how to decide whether they make any difference? Researchers disagree about where to place the boundaries between entrepreneurial ecosystems. To compare one entrepreneurial ecosystem with another, we must decide where entrepreneurs and new ventures belong. Researchers over-relying on public archival data available for relatively large geographic areas, i.e., states (NUTS-1) or regions (NUTS-2), at the expense of survey data about entrepreneurs’ values, beliefs, and attitudes gathered for smaller local areas, i.e., districts (NUTS-3), compound the problem. We propose to resolve the boundary problem with a new measurement approach. First , we gather self-reported and archival data at the district level. Second , we use systematic scale development procedures to validate congeneric measures that reflect EE elements. Third , the survey data helps to connect the micro and macro dimensions of EEs. Taken together, we move toward a measurement approach to reflect on whether local interventions can make a difference.L26;M13;R58;C1
A Cross‐Border Market Model with Limited Transmission Capacities
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We develop a cross‐border market model for two countries based on a continuous trading mechanism, in which the transmission capacities that enable transactions between market participants from different countries are limited. Our market model can be described by a regime‐switching process alternating between active and inactive regimes, in which cross‐border trading is possible, respectively prohibited. Starting from a reduced‐form representation of the two national limit order books, we derive a high‐frequency approximation of the microscopic model, assuming that the size of an individual order converges to zero while the order arrival rate tends to infinity. If transmission capacities are available, the limiting dynamics are as follows: the queue size processes at the top of the two limit order books follow a four‐dimensional linear Brownian motion in the positive orthant with oblique reflection at the axes. Each time the two best ask queues or the two best bid queues simultaneously hit zero, the queue size process is reinitialized. The capacity process can be described as a linear combination of local times and ishence of finite variation. The analytic tractability of the limiting dynamics allows us to compute key quantities of interest
Foundations of a learning system for food system transformation under uncertainty
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Despite a broad consensus on the necessity of fundamental change, endeavors to transform food systems appear to have reached an impasse. Greater engagement with the uncertainty of food systems could open up new ways of triggering transformation directed towards achieving more sustainable and inclusive outcomes. As a way of reorienting current food system change efforts to better embrace uncertainty, we propose a framework for a transformative learning system that serves two aims. First, the framework highlights the importance of locally led action, experimentation, and learning, providing a way of focusing on the core capacities and skills needed to act in the face of uncertainty. Second, it outlines the different types of learning functions that need to operate at different scales of food systems to trigger disruptive, coordinated, and more democratic change processes. The operationalization of this framework necessitates shifts in roles and ways of working across the landscape of food system interventions. The discussion will address the who and how of this potential change, as well as its subsequent impact on the operational modalities of individuals, the process of change itself, and the structures and institutions involved in the process. We argue that embracing uncertainty and the focus on learning has the potential to facilitate a more agile and locally relevant change process. This would allow actors to learn from decentrally pursued food systems reforms, leading to the emergence of diverse pathways that complement on-going efforts and potentially accelerate transformation efforts
Computing approximate Nash equilibria for integer programming games
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We propose a framework to compute approximate Nash equilibria in integer programming games with nonlinear payoffs, i.e. , simultaneous and non-cooperative games where each player solves a parametrized mixed-integer nonlinear program. We prove that using absolute approximations of the players’ objective functions and then computing its Nash equilibria is equivalent to computing approximate Nash equilibria where the approximation factor is doubled. In practice, we propose an algorithm to approximate the players’ objective functions via piecewise linear approximations. The numerical experiments on a cybersecurity investment game combined with a detailed analysis of the results show the computational effectiveness of our approach
Performance Appraisals, Works Councils and Employees’ Presenteeism Behaviour
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Presenteeism behaviour, that is, working despite illness, is a common phenomenon worldwide and can have severe consequences for employees and firms alike. In this study, we investigate the relationship between the use of company performance appraisals and employees’ presenteeism behaviour. We use linked‐employer–employee data (the German Linked Personnel Panel) and apply pooled Poisson as well as linear fixed effects panel estimations. We show that the use of performance appraisals is associated with significantly lower annual presenteeism days in the amount of half a day, which corresponds to a 10% difference from the base rate. The results are driven by performance appraisals that are linked to performance‐related pay, in particular. In addition, the significantly negative relationships between performance appraisals or performance pay and presenteeism only emerge when a works council is present at the workplace. Our study contributes to the understanding of employment relation‐specific behavioural consequences of management practices
Mixed-integer linear optimization for cardinality-constrained random forests
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Random forests are among the most famous algorithms for solving classification problems, in particular for large-scale data sets. Considering a set of labeled points and several decision trees, the method takes the majority vote to classify a new given point. In some scenarios, however, labels are only accessible for a proper subset of the given points. Moreover, this subset can be non-representative, e.g., due to collection bias. Semi-supervised learning considers the setting of labeled and unlabeled data and often improves the reliability of the results. In addition, it can be possible to obtain additional information about class sizes from undisclosed sources. We propose a mixed-integer linear optimization model for computing a semi-supervised random forest that covers the setting of labeled and unlabeled data points as well as the overall number of points in each class for a binary classification. Since the solution time rapidly grows as the number of variables increases, we present some problem-tailored preprocessing techniques and an intuitive branching rule. Our numerical results show that our approach leads to better accuracy and a better Matthews correlation coefficient for biased samples compared to random forests by majority vote, even if only a few labeled points are available
Child penalties in labour market skills
No full textThis paper estimates child penalties in labour-market-relevant cognitive skills, such as numeracy but also literacy and problem-solving competencies. We use international PIAAC data and adapt a pseudo-panel approach to a single cross-section covering 29 countries. Numeracy scores, which are associated with the largest returns to skills and pronounced gender differences, decline by 0.11 standard deviations for fathers and an additional 0.07 for mothers. We find no evidence of a deterioration in the occupational skill match for either mothers or fathers. Our findings suggest that changes in general labour market skills such as numeracy competencies explain at most 10% of child penalties in earnings. We additionally show that cross-sectional estimates of child penalties can be sensitive to controlling for predetermined characteristics that vary across cohorts, in our case education
CMAA–AHP: combinatorial multicriteria acceptability analysis with the analytic hierarchy process
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Combinatorial multi-criteria acceptability analysis (CMAA) is a framework for supporting multicriteria group decisions that provides both a detailed analysis of the effects of individual decision-maker inputs as well as interactive guidance for a consensus-building process. The analytical hierarchy process (AHP) is a widely-used model of decision-maker evaluations that is based on pairwise comparisons. The goal of this work is to show how CMAA can be integrated with AHP in order to make its benefits available to AHP users. We use a minimal input format for AHP which avoids a problem with inconsistency and also reduces the cognitive load on the decision-makers. We extend the CMAA method by introducing new judgement and preference sensitivity variables, which provide helpful insights for the facilitator of the group decision. An example illustrates the combined CMAA–AHP method and its ability to deliver consensus in a very small number of iterations. Monte Carlo simulation is used to study the convergence behavior of the method for a range of problem dimensions. It was found that the mean number of steps to reach consensus grows linearly with the number of alternatives and criteria. We consider two previously published group decisions that use the standard AHP approach of averaging decision-maker judgements and preferences. In both cases, CMAA–AHP delivers the same rankings based on the original input. However, the new method also provides insight into each decision and would have been able to guide each group to consensus within a small number of resolution steps
The Impact of Sandwich Care on Employment and Well-Being in Germany
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The provision of informal care has received a lot of attention during the past few decades. In the case of recurring parental care needs, adults may find themselves confronted with the task of juggling informal care for their parents and care for their children at the same time. These carers are typically called sandwich carers. Using data from the 2001–2019 waves of the German Socio-Economic Panel, we investigated the association between childcare, informal care, and sandwich care on labour earnings, work time, and self-rated health and life satisfaction of caregivers. Our results show that the provision of sandwich care, as well as an increase in care intensity, is associated with a reduction in labour earnings, working hours, and satisfaction with life. Additionally, we found that the effects for labour earnings and working hours also persisted for at least one wave after the provision of care. Analysing our data stratified by sex revealed that only women show significant decreases in their labour earnings and satisfaction with life if providing sandwich care. The combination of different types of care that is inherent in sandwich care comes with its own unique set of challenges and stressors for the carers. @Informelle Pflege hat in den letzten Jahrzehnten viel Aufmerksamkeit erhalten. In einigen Fällen finden sich Eltern von kleinen Kindern in der Situation wieder, dass die eigenen Eltern (oder andere nahestehende Personen) pflegebedürftig werden und sie die Pflege ihrer Eltern und die Betreuung ihrer Kinder gleichzeitig bewältigen müssen. Dies wird typischerweise als „Sandwichpflege“ bezeichnet. Die Kombination von Kinderbetreuung und informeller Pflege bringt ganz eigene Herausforderungen mit sich. Es ist naheliegend, dass diese Doppelbelastung deutliche Auswirkungen auf die Möglichkeiten hat, am Arbeitsmarkt zu partizipieren, und auch negative gesundheitliche Auswirkungen sind zu erwarten. Anhand von Daten aus den Wellen 2001–2019 des Sozioökonomischen Panels (SOEP) untersuchen wir die Auswirkungen von Kinderbetreuung, informeller Pflege und Sandwichpflege auf das Arbeitseinkommen, die Arbeitszeit, die selbsteingeschätzte Gesundheit und die Lebenszufriedenheit. Unsere Ergebnisse zeigen, dass Sandwichpflege, insbesondere wenn diese zeitintensiv ist, mit einer Verringerung des Arbeitseinkommens, der Arbeitszeit und der Lebenszufriedenheit verbunden ist. Darüber hinaus konnten wir feststellen, dass die Auswirkungen auf das Einkommen und die Arbeitszeit auch langfristig von Bedeutung sind. Es zeigt sich aber auch, dass ein signifikanter Rückgang des Einkommens und der Lebenszufriedenheit vor allem bei Frauen zu beobachten ist. Pflege ist bei Männern nur bedingt negativ. Insgesamt zeigt sich, dass Sandwichpflege, also die Kombination von Betreuung von Kindern und die Übernahme von Pflegeaufgaben, deutlich belastender ist als Pflege alleine und auch mit stärkeren negativen Auswirkungen auf den Arbeitsmarkt einhergeht