The degree to which different social groups get along is a key indicator of the cohesiveness of a society. This study examines perceptions of social cohesion among Europeans and explains variations in those perceptions by considering the separate and combined effects of economic strain and institutional trust. Analyses were conducted with the 27 member countries of the EU based on the Eurobarometer 74.1 on poverty and social exclusion conducted in 2010. Results show that individuals living in households experiencing economic strain perceive social cohesion to be weaker than their less economically hard‐pressed counterparts. By contrast, individuals trusting their political institutions perceived there to be higher levels of cohesion. Furthermore, institutional trust substantially moderates the negative relationship between economic strain and perceptions of cohesion. These results are robust to various model specifications. Moreover, extending the analysis revealed that this moderating effect held when considering social relations between the poor and rich and between different racial and ethnic groups. Theoretical and practical implications of the results are discussed.

Endogeneity is often regarded as a key barrier in establishing the causal relationship between the third sector and its societal impact in empirical research. Through a systematic literature review of the quantitative studies on the third sector’s impact in the last two decades, we find that most quantitative studies of the third sector’s societal impact are published in journals outside main third sector journals. We also offer specific examples of how recent methodological advancements in addressing endogeneity help third sector researchers better solve this problem. Based on the analysis of this literature review, we recommend that third sector scholars should (1) refocus on the big question of the third sector’s impact on society, (2) catch up with the methodological advancement in addressing endogeneity, (3) be creative and transparent about addressing endogeneity, and (4) build better theories to link the third sector to broad societal outcomes.

This paper presents a critical analysis of present approaches to studying not-for-profit performance reporting, and implications of research in this area. Focusing on three approaches: content analysis of publicly available performance reporting; quantitative analysis of financial data; and (rarer) mixed/other methods, we consider the impact of these on our knowledge of not-for-profit performance reporting, highlighting gaps and suggesting further research questions and methods. Our analysis demonstrates the important role of regulation in determining the research data available, and the impact of this on research methods. We inter-connect the methods, results and prevailing view of performance reporting in different jurisdictions and argue that this reporting has the potential to influence both charity practices and regulators’ actions. We call for further research in this interesting area. Contribution is made to the methodological literature on not-for-profits, and ongoing international conversations on regulating not-for-profit reporting.

Recent literature suggests that undergraduate students in political science dread studying methods, especially quantitative methods. Nonetheless, we believe that teaching students the value of quantitative analysis is critical. Going beyond traditional teaching approaches, we use a simulation to conceptualize the logic and process of quantitative analysis. In our simulation, student participants are told they are in a prison with another prisoner, where both have the objective to make the other prisoner crossover, using any strategy. The simulation allows students to generate and test basic hypothesis about students’ characteristics and their strategies, as well as operationalizing variables and quantifying results.

While there is an abundant use of macro data in the social sciences, little attention is given to the sources or the construction of these data. Owing to the restricted amount of indices or items, researchers most often apply the ‘available data at hand’. Since the opportunities to analyse data are constantly increasing and the availability of macro indicators is improving as well, one may be enticed to incorporate even qualitatively inferior indicators for the sake of statistically significant results. The pitfalls of applying biased indicators or using instruments with unknown methodological characteristics are biased estimates, false statistical inferences and, as one potential consequence, the derivation of misleading policy recommendations. This Special Issue assembles contributions that attempt to stimulate the missing debate about the criteria of assessing aggregate data and their measurement properties for comparative analyses.

Expert institutions are increasingly expected not only to provide the best professional expertise but also to ensure equal presence of women. Yet while descriptive gender representation in bureaucracies and courts is extensively researched, we largely lack studies of women’s presence on expert advisory bodies. Drawing on large-n data on the composition of Norwegian expert advisory commissions, the paper investigates and evaluates how the share of women on these commissions has developed over the last half-century. It finds that while overall gender parity was achieved in recent decades, women remain strongly under-represented among commission chairs, particularly academic chairs, and among academic members from the powerful economics discipline. Normatively speaking, the developments toward parity are promising, and we find no empirical indication that proportional representation and competence requirements are in tension. On the contrary, persistent gender gaps among economists on commissions and academic chairs may endanger adequate provision of expertise into policy-making.

The method of known additions for estimating clay-mineral content was reversed in that increasing proportions of soil clay were added to a standard composed of equal weights of kaolinite, illite, and montmorillonite. After glycolation, peak-area ratios were calculated from 7.2 (kaolinite), 10 (illite), 14 and 17 Å (vermiculite and montmorillonite) diffraction peaks of standard, mixes, and soil clay. Ratios were plotted against % soil clay from the standard (0%) through the mixes (14 to 77%). Curves of fit were calculated and projected to 100% soil clay giving theoretical values which agree with measured values. As weight proportions are known in the standard, the projections permit estimates of clay-mineral weight proportions in the soil clay.

The study aims to grasp the dynamic characteristics of paralinguistic communication during co-creation and has developed an analysis methodology by clustering the conversational patterns and determining the criteria more often observed in pre-resonance. The results suggest that pre-resonance is characterized by less silence, a rapid transition in exchanging ideas under one's initiative, and a conversation with equal amounts of utterances between both in a pair. This study reveals implications for better communication that lead to resonance, an essential phenomenon in collaborative design.

A new model for the interpretation of dioctahedral mica infrared (IR) spectra in the OH stretching vibration region is proposed. It is based on the analysis of the main factors responsible for the observed sequence of the OH frequencies. In terms of this model, the simple analytical dependence between the OH frequencies and the mass and valency of cations bonded to OH groups has been found. The specific character of the interaction between octahedral Al and OH groups in the mica structures is assumed.

Integrated optical densities of the OH bands determined by the decomposition of the studied mica IR spectra are used for the quantitative analysis, that is, for the determination of a number of each type of octahedral cations per unit cell of the sample under study. A good agreement between the octahedral cation contents of 2:1 layers found from the IR spectra decomposition and the chemical analysis has shown that this technique may be used to study the local order-disorder of isomorphous cation distribution in mica structures.

The essential result obtained by the quantitative analysis of the mica IR spectra is the determination of Fe3+ cations in the tetrahedral sites of some samples. This means that the conventional presentation of structural formulae for Al-Fe3+-containing 2:1 layer silicates is unacceptable without consideration of tetrahedral Fe3+ by spectroscopic techniques and by the quantitative analysis of the IR spectra, in particular.

It is usual in Mössbauer spectroscopy analysis to take the subspectra areas as a measure of the concentration of the Fe compounds that generate them. In soils, the presence of different-size particles of different nature makes the semiquantitative Mössbauer studies difficult, and some handling of the sample must be carried out in order to get reliable area results (Bowman et al. 1967; Muir 1968; Williamson et al. 1981).

Investigation of a naturally occurring mixture of dioctahedral micas prompted an examination of X-ray diffraction (XRD) techniques for obtaining quantitative estimates of 1M and 2M 1 mica proportions. A method for determining quantitative estimates has been developed that includes the effect of preferred orientation of mica particles as described by the March function. A diagram is presented from which the percentage of 2Mı and the March parameter (r) can be obtained from two peak-area ratios: 2.80 Å/5.0 Å and 2.80 Å/2.58 Å, which are measured on observed XRD patterns of mica mixtures. The ability of this peak-area ratio diagram to predict reasonably accurate proportions of 1M and 2Mı micas was tested by comparing calculated and observed XRD patterns over a range of 2θ values from 16° to 40° for size-fractionated mixtures. Lack of accurate crystal-structure data for dioctahedral 1M mica proved an impediment to obtaining improved quantitative estimates of mica proportions.

An internal standard X-ray diffraction (XRD) analysis technique permits reproducible and accurate calculation of the mineral contents of rocks, including the major clay mineral families: Fe-rich chlorites + berthierine, Mg-rich chlorites, Fe-rich dioctahedral 2:1 clays and micas, Al-rich dioctahedral 2:1 clays and micas, and kaolinites. A single XRD pattern from an air-dried random specimen is used. Clays are quantified from their 060 reflections which are well resolved and insensitive to structural defects. Zincite is used as the internal standard instead of corundum, because its reflections are more conveniently located and stronger, allowing for a smaller amount of spike (10%). The grinding technique used produces powders free of grains coarser than 20 µm and suitable for obtaining random and rigid specimens.

Errors in accuracy are low, <2 wt. % deviation from actual values for individual minerals, as tested on artificial shale mixtures. No normalization is applied and thus, for natural rocks, the analysis is tested by the departure of the sum of the measured components from 100%. Our approach compares favorably with other quantitative analysis techniques, including a Rietveld-based technique.

Details of the quantitative techniques successfully applied to artificial rock mixtures distributed for the third Clay Minerals Society Reynolds Cup (RC) contest are presented. Participants each received three samples, two containing 17 minerals each and a third containing ten minerals. The true composition of the samples was unknown to all participants during the contest period. The results submitted were ranked by summing the deviations from the actual compositions (bias). The top three finishers used mainly X-ray diffraction (XRD) for identification and quantification. The winner obtained an average bias of 11.3% per sample by using an internal standard and modified single-line reference intensity ratio (RIR) method based on pure mineral standards. Full-pattern fitting by genetic algorithm was used to measure the integrated intensity of the diagnostic single-line reflections chosen for quantification. Elemental-composition optimization was used separately to constrain phase concentrations that were uncertain because the reference mineral standards were lacking or not ideal. Cation exchange capacity, oriented-sample XRD analysis, and thermogravimetric analysis were also used as supplementary techniques. The second-place finisher obtained an average bias of 13.9%, also by using an RIR method, but without an added internal standard and with intensity measured by whole-pattern fitting. The third-place finisher, who obtained an average bias of 15.3%, used the Rietveld method for quantification and identification of minor phases (using difference plots). This participant also used scanning electron microscopy (with X-ray microanalysis) to identify minor components and verify the composition of structures used in Rietveld analysis. As in the previous contests, successful quantification appears to be more dependent on analyst experience than on the analytical technique or software used.

In 2000, The Clay Minerals Society established a biennial quantitative mineralogy round robin. The so-called Reynolds Cup competition is named after Bob Reynolds for his pioneering work in quantitative clay mineralogy and exceptional contributions to clay science. The first contest was run in 2002 with 40 sets of three samples, which were prepared from mixtures of purified, natural, and synthetic minerals that are commonly found in clay-bearing rocks and soils and represent realistic mineral assemblages. The rules of the competition allow any method or combination of methods to be used in the quantitative analysis of the mineral assemblages. Throughout the competition, X-ray diffraction has been the method of choice for quantifying the mineralogy of the sample mixtures with a multitude of other techniques used to assist with phase identification and quantification. In the first twelve years of the Reynolds Cup competition (2002 to 2014), around 14,000 analyses from 448 participants have been carried out on a total of 21 samples. The data provided by these analyses constitute an extensive database on the accuracy of quantitative mineral analyses and also has given enough time for the progression of improvements in such analyses. In the Reynolds Cup competition, the accuracy of a particular quantification is judged by calculating a “bias” for each phase in an assemblage. Determining exactly the true amount of a phase in the assemblage would give a bias of zero. Generally, the higher placed participants correctly identified all or most of the mineral phases present. Conversely, the worst performers failed to identify or misidentified phases. Several contestants reported a long list of minor exotic phases, which were likely reported by automated search/match programs and were mineralogically implausible. Not surprisingly, clay minerals were among the greatest sources of error reported. This article reports on the first 12 years of the Reynolds Cup competition results and analyzes the competition data to determine the overall accuracy of the mineral assemblage quantities reported by the participants. The data from the competition were also used to ascertain trends in quantification accuracy over a 12 year period and to highlight sources of error in quantitative analyses.