The significance of meaning. Why IPBES needs the social sciences and humanities

The term “biodiversity” is often used to describe phenomena of nature, which can be studied without a reference to the socially constructed, evaluative, or indeed normative contexts. In our paper, we challenge this conception by focusing particularly on methodological aspects of biodiversity research. We thereby engage with the idea of interdisciplinary biodiversity research as a scientific approach directed at the recognition and management of contemporary society in its ecological embedding. By doing this, we explore how research on and assessments of biodiversity can be enhanced if meaning, aspiration, desires, and related aspects of agency are methodically taken into account. In six sections, we substantiate our claim that the discourse on biodiversity (including the IPBES (Intergovernmental science-policy Platform on Biodiversity and Ecosystem Services) debate) is incomplete without contributions from the social sciences and humanities. In the introduction, a brief overview of biodiversity’s conceptual history is provided showing that “biodiversity” is a lexical invention intended to create a strong political momentum. However, that does not impede its usability as a research concept. Section 2 examines the origins of the Convention on Biological Diversity (CBD) by way of sociological discourse analysis. Subsequently, it proposes a matrix as a means to structure the ambiguities and tensions inherent in the CBD. The matrix reemphasizes our main thesis regarding the need to bring social and ethical expertise to the biodiversity discourse. In Section 3, we offer a brief sketch of the different methods of the natural and social sciences as well as ethics. This lays the groundwork for our Section 4, which explains and illustrates what social sciences and ethics can contribute to biodiversity research. Section 5 turns from research to politics and argues that biodiversity governance necessitates deliberative discourses in which participation of lay people plays an important role. Section 6 provides our conclusions.     

The frontline delivery of activation: workers’ preferences and their antecedents

This article intends to contribute to the increasing body of academic literature on the frontline delivery of activation policies. In line with the broader literature on frontline work, this literature focuses attention on frontline delivery practices and preferences and how these can be explained. Activation work is an interesting case in this context, because activation workers’ jobs designs vary considerably and workers have a diversity of educational backgrounds (including but not limited to social work) in the many countries that have implemented activation policies. This article looks at workers’ preferences rather than actual delivery practices. It analyses how job design and educational background are related to workers’ preferences concerning servicing clients, managing activation workers and spending time on various activation-related activities. Although the findings of the research that are presented in the article show that educational background and job design play only a modest role as antecedents of workers’ preferences, future research into this issue remains interesting. For it may help to increase our insights into the optimal match between what activation aims to achieve and how the provision of activation is organized on the one hand, and workers’ skills/qualifications and job design on the other hand.     

Gender and social conformity: Do men and women respond differently to social pressure to vote?

In this paper, we re-analyze data from a large-scale field experiment (N = 344,084) on voter turnout in order to determine whether men and women respond differently to social pressure aimed at voter mobilization. To date, there have been mixed results regarding the interaction between a person’s gender and receptivity to social influence. On the whole, our analyses confirm prior findings that social pressure increases voter turnout but uncover little to no evidence of gender differences in receptivity to social pressure cues in the context of political participation.     

Estimates of subgroup treatment effects in overall nonsignificant trials: To what extent should we believe in them?

In drug development, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population but appears to be beneficial in a relevant subgroup. In case the subgroup of interest was not part of a confirmatory testing strategy, the inflation of the overall type I error is substantial and therefore such a subgroup analysis finding can only be seen as exploratory at best. To support such exploratory findings, an appropriate replication of the subgroup finding should be undertaken in a new trial. We should, however, be reasonably confident in the observed treatment effect size to be able to use this estimate in a replication trial in the subpopulation of interest. We were therefore interested in evaluating the bias of the estimate of the subgroup treatment effect, after selection based on significance for the subgroup in an overall “failed” trial. Different scenarios, involving continuous as well as dichotomous outcomes, were investigated via simulation studies. It is shown that the bias associated with subgroup findings in overall nonsignificant clinical trials is on average large and varies substantially across plausible scenarios. This renders the subgroup treatment estimate from the original trial of limited value to design the replication trial. An empirical Bayesian shrinkage method is suggested to minimize this overestimation. The proposed estimator appears to offer either a good or a conservative correction to the observed subgroup treatment effect hence provides a more reliable subgroup treatment effect estimate for adequate planning of future studies.     

A socio-ecological perspective of urban green networks: the Stockholm case

Landscape fragmentation threatens habitats, biodiversity and other ecosystem services. In tackling this threat, the dynamic processes of social-ecological systems should be recognised and understood. Although network analysis based on graph theory has been recognised as an efficient way of spatially understanding landscape or habitat connectivity, only few studies have offered specific approaches or suggestions for integrating detailed social-ecological values into geographical distributions. As a contribution to bridging this gap, this paper introduces a social-ecological network model for the issue of landscape or habitat fragmentation applied to the case of Stockholm, Sweden. Graph theory was used in combination with sociotope and biotope maps for simple visualisation of network situations in two-dimensional maps. The European crested tit (Lophophanes cristatus), European common toad (Bufo bufo) and human beings were selected as indicator species, based on a landscape ecology analysis in Stockholm Municipality in 2009. Slope, land use and human disturbance maps were assessed in order to decide cost values of travelling from node to node. Lease-cost-path accumulation was used to create ideal reference maps of green networks. Three separate maps were then developed for suggesting efficient routes for three indicators in city scale that mainly connect from the Royal National City Park to the other parts of the city. The model in Hjorthagen neighbourhood to highlight two practical paths that link this fragmented community to its neighbouring park areas. Findings make it possible to address two scales of network improvement strategies, namely first for the city-scale green network that connects geographical habitats (nodes) and the regional green wedges of the city, and the second that of neighbourhood links between habitats in detailed layers of green networks. Strategic improvement potentials are presented based on ideal reference maps of green networks correspondingly.     

Who is leading the campaign charts? Comparing individual popularity on old and new media

Attention in the mass media is seen as crucial for electoral success. However, most ordinary candidates hardly get any attention in the news. With social media outlets becoming ever more popular, the question is whether the overall asymmetry in attention for candidates still holds today. Do candidates who dominate the traditional media during the campaign also dominate the social media? Or can candidates make up for a lack of mass media coverage by attracting attention on these new media platforms? This paper aims to answer these questions by pairing Twitter activity and Twitter popularity with newspaper attention for a large number of individual candidates in the 2014 Belgian election campaign. We expand the normalization versus equalization debate by not only looking at how much a new medium is used, but also at its success in terms of popularity and audience reach. Our findings show that the two platforms are indeed related, mainly because a small political elite dominates both old and new media. Twitter popularity and Twitter activity (albeit to a lesser extent) are higher among powerful politicians. We elaborate on why these findings are so much in line with the normalization hypothesis.     

Differences between paid and unpaid social services for beneficiaries

In many Western welfare states, social work services that have traditionally been provided by paid employees are being replaced by family support, community support, informal networks, and volunteering. For the field of social work, it is relevant to know what it matters to beneficiaries whether services are provided by volunteers or by paid employees. The central question of this article is therefore as follows: What are the differences between unpaid and paid social services for beneficiaries? The article is based on literature review and focus groups. Our results suggest that beneficiaries do experience some differences regarding the advantages of volunteer services for beneficiaries that can be summarized in three propositions: (1) services provided by volunteers are more relational than are services provided by paid employees, and they are therefore perceived as more equal, flexible and sincere. (2) The effects of volunteer services for beneficiaries are not exclusively positive. (3) Although particular tasks may appear to be interchangeable to some extent, the relative advantages of a given task depend upon whether it is performed by a paid worker or by a volunteer. Additional research is needed in order to provide further validation.     

Impact of Race on the Implementation of Empirically Supported Treatments in Substance Abuse Treatment

The effort to address the gap between research and practice in substance abuse treatment has largely neglected the role of local resources and political trends. This study seeks to clarify the role of the local environment in implementing empirically supported treatments (ESTs). The study consisted of secondary data analysis of substance abuse treatment centers (N = 13,079) and U.S. Census data to determine the likelihood of using EST by substance abuse treatment centers in counties with 50% or more Black residents. Bivariate and multivariate models were employed. After controlling for various factors, results indicate that substance use disorder treatment agencies that accept federal funding are less likely to use ESTs if they are located in counties with predominantly (> 50%) Black residents. Implementation of ESTs could be influenced by community racial distribution (% Black), but environmental constraints and events might shift implementation patterns.     

Functional analysis of high-content high-throughput imaging data

High-content automated imaging platforms allow the multiplexing of several targets simultaneously to generate multi-parametric single-cell data sets over extended periods of time. Typically, standard simple measures such as mean value of all cells at every time point are calculated to summarize the temporal process, resulting in loss of time dynamics of the single cells. Multiple experiments are performed but observation time points are not necessarily identical, leading to difficulties when integrating summary measures from different experiments. We used functional data analysis to analyze continuous curve data, where the temporal process of a response variable for each single cell can be described using a smooth curve. This allows analyses to be performed on continuous functions, rather than on original discrete data points. Functional regression models were applied to determine common temporal characteristics of a set of single cell curves and random effects were employed in the models to explain variation between experiments. The aim of the multiplexing approach is to simultaneously analyze the effect of a large number of compounds in comparison to control to discriminate between their mode of action. Functional principal component analysis based on T-statistic curves for pairwise comparison to control was used to study time-dependent compound effects.