Improving the Value of Standard Toxicity Test Data in REACH

Worldwide, environmental risk assessment strategies are based on the assumption that measuring direct effects of single substances, using a few single species tests, in combination with safety factors correcting for extrapolation inconsistencies, can be used to protect higher levels of biological organization, such as populations and even ecosystems. At the same time, we are currently facing a range of pollution problems (Millennium Ecosystem Assessment Series 2005), of which some could at least indirectly be linked to the fact that this assumption may not be fully valid. Consequently, there is an ongoing scientific debate on whether current chemical control protocols are sufficient for protection of ecosystems, and numerous suggestions for improvements have been presented by the scientific community, e.g. alternative tests and testing strategies. On the other hand, few of these suggestions actually reach the regulatory world (or become implemented), and risk assessment today basically follows the same paradigm as 30 years ago. While the new REACH regime is exceptionally ambitious, this chapter observes several problems and gaps in this regulatory framework. We suggest measures and approaches which imply increased ecological realism and understanding in future regulatory work

Many Labs 2: Investigating Variation in Replicability Across Samples and Settings

We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely highpowered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Sociales::Instituto de Investigaciones Psicológicas (IIP