59 research outputs found
Land Policy for Flood Risk Management-Toward a New Working Paradigm
Flood risk management (FRM) aims to integrate necessary technical measures with environmental and societal approaches. Focusing on the process and governance of how to plan, implement, and maintain solutions therefore becomes essential. Among the different stakeholders, landowners are a key group to be considered. This contribution elaborates on the interconnections between land policy, FRM and private land ownership. It is based on the European COST Action network LAND4FLOOD, which brings together academics and stakeholders from various disciplines and more than 35 countries. We argue for a less project oriented and more process oriented approach, a focus on land management and more emphasis on small-scale measures. This represents a break with some of the recent working paradigms of FRM
Tradeoffs and synergies in wetland multifunctionality: A scaling issue
Wetland area in agricultural landscapes has been heavily reduced to gain land for crop production, but in recent years there is increased societal recognition of the negative consequences from wetland loss on nutrient retention, biodiversity and a range of other benefits to humans. The current trend is therefore to re-establish wetlands, often with an aim to achieve the simultaneous delivery of multiple ecosystem services, i.e., multifunctionality. Here we review the literature on key objectives used to motivate wetland re-establishment in temperate agricultural landscapes (provision of flow regulation, nutrient retention, climate mitigation, biodiversity conservation and cultural ecosystem services), and their relationships to environmental properties, in order to identify potential for tradeoffs and synergies concerning the development of multifunctional wetlands. Through this process, we find that there is a need for a change in scale from a focus on single wetlands to wetlandscapes (multiple neighboring wetlands including their catchments and surrounding landscape features) if multiple societal and environmental goals are to be achieved. Finally, we discuss the key factors to be considered when planning for re-establishment of wetlands that can support achievement of a wide range of objectives at the landscape scale
A many-analysts approach to the relation between religiosity and well-being
The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates
A Many-analysts Approach to the Relation Between Religiosity and Well-being
The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates
A many-analysts approach to the relation between religiosity and well-being
The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates
Unreliable heterogeneity:how measurement errorobscures heterogeneity in meta-analyses inpsychology
Measurement error (imperfect reliability) is present in any empirical effect size estimate and system-atically attenuates observed effect sizes compared to true underlying effect sizes. Yet there exist broad concerns thatproper measurement tends to be neglected in much of psychological research. We examined how measurement errorin primary studies affects meta-analytic heterogeneity estimates using Monte-Carlo simulations. Our results indicatethat although measurement error in primary studies can both inflate and suppress heterogeneity, under most circum-stances measurement error in primary studies leads to a severe underestimate of heterogeneity in meta-analysis. Oursimulations showed expected heterogeneity to be underestimated by about 15% - 60% when considering a typicaleffect size around r = 0.2 and true heterogeneity levels that are common in the meta-analytic literature ( >0.1, inPearson’s r). The underestimate primarily depends on average reliability in primary studies (higher reliability leadsto a smaller underestimate), but also worsens with smaller primary study sample sizes. We observed a positive biasin heterogeneity estimates due to measurement error only under specific and arguably uncommon circumstancesof (1) actual zero heterogeneity, particularly when mean effect sizes are large, or (2) combinations of very smalltrue heterogeneity, large variance in primary study reliabilities, large mean effect sizes, and a limited number ofprimary studies. Severe underestimates of heterogeneity due to measurement error may affect many meta-analysesin psychology and obscure true differences between studies that could be relevant for theory, practice, and futureresearch efforts. Research on concrete guidance to applied meta-analysts is needed, as sophisticated methods for cor-recting measurement unreliability such as meta-analytic structural equation modeling (MASEM) are only applicablein exceptional cases and corrections based on classical test theory come with caveats and strong assumptions
The prevalence of marginally significant results in psychology over time
We examined the percentage of p values (.05 < p ≤ .10) reported as marginally significant in 44,200 articles, across nine psychology disciplines, published in 70 journals belonging to the American Psychological Association between 1985 and 2016. Using regular expressions, we extracted 42,504 p values between .05 and .10. Almost 40% of p values in this range were reported as marginally significant, although there were considerable differences between disciplines. The practice is most common in organizational psychology (45.4%) and least common in clinical psychology (30.1%). Contrary to what was reported by previous researchers, our results showed no evidence of an increasing trend in any discipline; in all disciplines, the percentage of p values reported as marginally significant was decreasing or constant over time. We recommend against reporting these results as marginally significant because of the low evidential value of p values between .05 and .10
On cross‐linguistic variation and measures of linguistic complexity in learner texts: Italian, French and English
The paper investigates possible effects of cross‐linguistic variation on measures of syntactic complexity in 60 texts from Swedish L1 learners of English, French and Italian as foreign languages at CEFR level A and CEFR level B. A previous study on the same learners and texts, showed significant differences between proficiency levels for two length measures of complexity in English and French, but not in Italian. In this paper we hypothesize that due to the Null Subject property of Italian, the developmental prediction for some complexity measures might be different in Italian compared to French and English. In fact, previous research has suggested that beginner learners of Italian overuse overt subjects which might lead to higher scores, relatively speaking, of length measures in Italian at the lowest levels of proficiency. However, contrary to our hypothesis, we did not find more Null subjects at CEFR level B than at CEFR level A, but we did find clear restrictions on their distribution. We conclude that we are a long way from understanding how cross‐linguistic differences interact with other variables such as tasks and language combinations and what the effects might be on measures of syntactic complexity
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