Several influential publications have sensitized the community of behavioral scientists to the dangers of inflated effects and false-positive errors leading to the unwarranted publication of nonreplicable findings. This issue has been related to prominent cases of data fabrication and survey results pointing to bad practices in empirical science. Although we concur with the motives behind these critical arguments, we note that an isolated debate of false positives may itself be misleading and counter-productive. Instead, we argue that, given the current state of affairs in behavioral science, false negatives often constitute a more serious problem. Referring to Wason's (1960) seminal work on inductive reasoning, we show that the failure to assertively generate and test alternative hypotheses can lead to dramatic theoretical mistakes, which cannot be corrected by any kind of rigor applied to statistical tests of the focal hypotheses. We conclude that a scientific culture rewarding strong inference (Platt, 1964) is more likely to see progress than a culture preoccupied with tightening its standards for the mere publication of original findings.

The idea of money reminds consumers of personal strength and resources. Such cues have been found to increase the level of mental construal. Consequently, it was hypothesized and found in five experiments that reminders of money trigger abstract (vs. concrete) mental construals. Participants were primed with money or money-unrelated concepts. Money primes caused a preference for abstract over concrete action identifications (experiment 1), instigated the formation of broader categories (experiment 2), and facilitated the identification of global (vs. local) aspects of visual patterns (experiment 3). This effect extended to consumer judgments: money primes caused a focus on central (vs. peripheral) aspects of products (experiment 4) and increased the influence of quality of parent brands in evaluations of brand extensions. Priming with a little money (experiment 3) or expenditures (experiment 5) did not trigger abstract construals, indicating that the association between money and resources drives the effect.

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Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductivelearning constraints imposed on decisions from experience.

Changing defaults—the preselection that becomes effective without active choice—is becoming a prominent policy tool, after having been proven to be effective in areas as varied as retirement savings, organ donation and product customization. Yet, little is known about how default effects spill over to subsequent similar behaviors. In an online shopping scenario, we found standard default effects on the share of organically produced products in the overall selection of products. These effects did not spill over to subsequent active shopping choices. This was true for defaults that were hard and easy to change (Exp. 1, N = 90), for immediate and delayed subsequent choices (Exp. 2, N = 106) and for self‐selected defaults (Exp. 3, N = 181). These findings suggest that the reach and scalability of default manipulations in policy making may be limited, but also speak against the possibility for negative spillover.