loopUI-0.1: uncertainty indicators to support needs and practices in 3D geological modelling uncertainty quantification

To support the needs of practitioners regarding 3D geological modelling and uncertainty quantification in the field, in particular from the mining industry, we propose a Python package called loopUI-0.1 that provides a set of local and global indicators to measure uncertainty and features dissimilarities among an ensemble of voxet models. Results are presented of a survey launched among practitioners in the mineral industry, enquiring about their modelling and uncertainty quantification practice and needs. It reveals that practitioners acknowledge the importance of uncertainty quantification even if they do not perform it. Four main factors preventing practitioners to perform uncertainty quantification were identified: lack of data uncertainty quantification, (computing) time requirement to generate one model, poor tracking of assumptions and interpretations, relative complexity of uncertainty quantification. The paper reviews and proposes solutions to alleviate these issues. Elements of an answer to these problems are already provided in the special issue hosting this paper and more are expected to come.

Are SDG s Counting What Counts?

The 2030 Agenda for Sustainable Development (Agenda 2030) encompasses social, economic, and environmental commitments within a single global framework. However, experts have been warning that the ambitious nature of Agenda 2030’s Sustainable Development Goals (SDG s) might be lost in indicator-driven implementation. This article examines the assumption that SDG indicators result in policy shrinking (offering a less ambitious framing) by exploring how the framing of Agenda 2030’s gender commitments shifts from SDG s to their indicators. Employing critical frame analysis, this article shows that SDG global indicators result in policy shrinking of gender-specific targets in terms of their 1) human rights framing 2) overall scope, and 3) inclusivity of target groups. This policy shrinking does not necessarily undermine Agenda 2030, but it does call for greater attention, especially by actors promoting gender equality, to national interpretations of specific SDG targets and the inclusivity of otherwise marginalized policy target groups.

Automatic delimitation of labour market areas based on multi-criteria optimisation: The case of Spain 2011

Labour market areas (LMAs) are a type of functional region (FR) defined on commuting flows and used in many countries to serve as the territorial reference for regional studies and policy making at local levels. Existing methods rely on manual adjustments of the results to ensure high quality, making them difficult to be monitored, hard to apply to different territories, and onerous to produce in terms of required work-hours. We propose an approach to automatise all stages of the delineation procedure and improve the final results, building upon a state-of-the-art stochastic search procedure that ensures optimal allocation of municipalities/counties to LMAs while keeping good global indicators: a pre-processing layer clusters adjoining municipalities with strong commuting flows to constrain the initial search space of the stochastic search, and a multi-criteria heuristic corrects common deficiencies that derive from global maximisation approaches or simple greedy heuristics. It produces high quality LMAs with optimal local characteristics. To demonstrate this methodology and assess the improvement achieved, we apply it to define LMAs in Spain based on the latest commuting data.

Hazards and fallacies of social measurements: global indicators in the pandemic

Since the outbreak of the COVID-19 pandemic, efforts to quantitatively measure the global health situation and/or governments’ reaction vis-à-vis the pandemic have flourished. In spite of the significance of data in the fight against the pandemic, however, such global knowledge is largely questionable, insofar as it exposes itself to the many hazards and fallacies associated with global attempts to frame the social world in numbers. This is why the paper attempts to identify the hazards and fallacies most commonly associated with global measurements of social phenomena and to verify whether and to what extent these hazards and fallacies affect numerical representations of the pandemic and its effects. To this end, the paper analyses ten English-language global numerical initiatives that were launched between January and May 2020, and reviews them in light of existing critical literature on global numbers. The aim is to provide a deeper understanding of global measurements of health and related law-and-policy measures, and to suggest caution about their use as a basis for knowledge and action in the context of the pandemic.

The impact of foreign public evaluations of the US Presidents on the favorability toward the country

This study examines how international publics’ evaluations of US Presidents affect the favorability of their views of the US. More specifically, it investigates the impact of the US Presidents George W. Bush, Barak Obama and Donald Trump on attitudes toward the US in 32 nations. It analyzes the data from Pew Research Center’s Global Indicators Database on opinions of the US and confidence in the US President from 2002 to 2018. The analysis reveals a significant relationship between confidence in the US Presidents and favorable attitudes toward the US among foreign publics. The paper further discusses the implications of global evaluations of US Presidents for US public diplomacy.

Sanctification of marriage, religious coping and marital adjustment of Iranian couples

This study examined cross-sectional links of the theistic and non-theistic sanctification of marriage and positive and negative religious coping with marital adjustment for 316 married Muslims (women = 157, men = 159) from Iran. Perceiving marriage to be a manifestation of God (i.e. theistic sanctification) and reflective of sacred qualities (i.e. non-theistic sanctification) as well as engaging in positive and negative religious/spiritual (r/s) coping strategies each uniquely contributed variance to marital adjustment, after controlling for each other and global indicators of devotion to Islam (e.g. frequency of prayer, religious pilgrimages, fasting, reciting the Quran), and demographic variables (e.g. education level). Specifically, theistic sanctification (β = .40), non-theistic sanctification (β = .29), and positive r/s coping (β = .56) were uniquely tied to higher marital adjustment whereas negative r/s coping was uniquely tied to lower marital adjustment theistic (β =-15) in a hierarchical regression model with all primary variables and controls entered. These findings replicate and extend prior findings on the perceived sanctity of marriage with US samples of predominantly Christians to Muslims living in the Middle East, and offer novel cross-cultural insights into the possible roles that sanctification of marriage and r/s coping may play for marital well-being for non-distressed married Muslims.

Risk Analysis of Regions with Suspicious Illegal Logging and Their Trade Flows

To eradicate illegally harvested wood sources in its domestic market, it is critical to conduct risk assessments on wood sourcing in regions with illegal loggings. It is not reliable to use a single indicator to analyze suspicious illegal logging. This study integrates three key global indicators: CPI (Corruption Perceptions Index), HDI (Human Development Indicator), and WGI (The Worldwide Governance Indicators) by applying the entropy weight method to establish a new risk indicator to rank suspicious illegal logging regions. This study aims to establish better risk indicators by considering more factors to assess the risks of illegal logging and its trade flow more reliably. By analyzing roundwood production, Myanmar, Congo, and Nigeria are rated high-risk. Countries such as the U.S., Germany, Canada, and Finland are rated low-risk.

Combined Correlation and Cluster Analysis for Long-Term Power Quality Data from Virtual Power Plant

Analysis of the connection between different units that operate in the same area assures always interesting results. During this investigation, the concerned area was a virtual power plant (VPP) that operates in Poland. The main distributed resources included in the VPP are a 1.25 MW hydropower plant and an associated 0.5 MW energy storage system. The mentioned VPP was a source of synchronic, long-term, multipoint power quality (PQ) data. Then, for five related measurement points, the conclusion about the relation in point of PQ was performed using correlation analysis, the global index approach, and cluster analysis. Global indicators were applied in place of PQ parameters to reduce the amount of analyzed data and to check the correlation between phase values. For such a big dataset, the occurrence of outliers is certain, and outliers may affect the correlation results. Thus, to find and exclude them, cluster analysis (k-means algorithm, Chebyshev distance) was applied. Finally, the correlation between PQ global indicators of different measurement points was performed. It assured general information about VPP units’ relation in point of PQ. Under the investigation, both Pearson’s and Spearman’s rank correlation coefficients were considered.