The observation of behaviour is a key theoretical parameter underlying a number of models of prosociality. However, the empirical findings showing the effect of observability on prosociality are mixed. In this meta-analysis, we explore the boundary conditions that may account for this variability, by exploring key theoretical and methodological moderators of this link. We identified 117 papers yielding 134 study level effects (total n = 788 164) and found a small but statistically significant, positive association between observability and prosociality (r = 0.141, 95% confidence interval = 0.106, 0.175). Moderator analysis showed that observability produced stronger effects on prosociality: (i) in the presence of passive observers (i.e. people whose role was to only observe participants) versus perceptions of being watched, (ii) when participants’ decisions were consequential (versus non-consequential), (iii) when the studies were performed in the laboratory (as opposed to in the field/online), (iv) when the studies used repeated measures (instead of single games), and (v) when the studies involved social dilemmas (instead of bargaining games). These effects show the conditions under which observability effects on prosociality will be maximally observed. We describe the theoretical and practical significance of these results.

Reducing methane emissions from the oil and gas industry is a critical climate action policy tool in Canada and the US. Optical gas imaging-based leak detection and repair (LDAR) surveys are commonly used to address fugitive methane emissions or leaks. Despite widespread use, there is little empirical measurement of the effectiveness of LDAR programs at reducing long-term leakage, especially over the scale of months to years. In this study, we measure the effectiveness of LDAR surveys by quantifying emissions at 36 unconventional liquids-rich natural gas facilities in Alberta, Canada. A representative subset of these 36 facilities were visited twice by the same detection team: an initial survey and a post-repair re-survey occurring ∼0.5-2 years after the initial survey. Overall, total emissions reduced by 44% after one LDAR survey, combining a reduction in fugitive emissions of 22% and vented emissions by 47%. Furthermore, >90% of the leaks found in the initial survey were not emitting in the re-survey, suggesting high repair effectiveness. However, fugitive emissions reduced by only 22% because of new leaks that occurred between the surveys. This indicates a need for frequent, effective, and low-cost LDAR surveys to target new leaks. The large reduction in vent emissions is associated with potentially stochastic changes to tank-related emissions, which contributed ∼45% of all emissions. Our data suggest a key role for tank-specific abatement strategies as an effective way to reduce oil and gas methane emissions. Finally, mitigation policies will also benefit from more definitive classification of leaks and vents.

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Employability is a key concern for students and it is of increasing importance to universities with the inclusion of employability outcomes affecting performance in league tables and in the Teaching 3 Excellence Framework. Universities typically teach employability either by embedding it within a 4 course curriculum (embedded approach) or via the career services (parallel approach). This article 5 explores the ratio of United Kingdom (UK) Psychology departments adopting an embedded approach vs a parallel approach to employability and investigates how Psychology students within a parallel department engage with their careers service. A survey of 258 undergraduate psychology students finds low levels of engagement with career service events, typically less than 50% attendance, despite increases in attendance over the course of student's degree. These findings highlight how many students, in a parallel department are simply not attending events designed to help them explore their career options or assist them navigating the application process.

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Globally, many millions of animals are used by humans every year and much of this usage causes public concern. A new scale, devised to measure attitudes to animal use in relation to the purpose of use and species, the Animal Purpose Questionnaire (APQ), was completed by in total 483 participants, 415 British nationals and 68 participants from 39 other countries. The APQ was presented in two survey formats, alongside an established Animal Attitudes Scale (AAS). In both surveys, participants also provided demographic details to provide a context to their attitudes to animals. As might be expected, and consistent with the validity of the new scale, overall scores on the AAS and APQ were highly correlated. However, the APQ provided a more differentiated measure of attitudes to animal use across a variety of settings. The results showed that there was overall higher levels of agreement with the use of animals in medical research and basic science, less endorsement for food production and pest control, and the use of animals for other cultural practices was generally disapproved of, irrespective of species. Participants overall disagreed with the use of rabbits, monkeys, badgers, tree shrews (survey 1), chimpanzees, dogs, dolphins and parrots (survey 2), but were neutral about the use of rats, mice, pigs, octopus, chickens, zebrafish (survey 1), carp, chickens, pigs, pigeons, rabbits and rats (survey 2). Interactions between species and purpose were largely driven by the consideration of using diverse species for food production. In general, females and vegetarians expressed less agreement with the use of animals with some differences by purpose of use. Pet keeping consistently predicted reduced willingness to use animals for basic science (only). The APQ provides a new tool to unpack how public attitudes depend on the intersectionality of demographics, species and purpose of use.

The ubiquitous use of the internet for all manner of daily tasks means that there are now large reservoirs of data that can provide fresh insights into human behaviour. One of the key barriers preventing more researchers from utilising online data is that researchers do not have the skills to access the data. This tutorial aims to address this gap by providing a practical guide to web scraping online data using the popular statistical language R. Web scraping is the process of automatically collecting information from websites, which can take the form of numbers, text, images or videos. In this tutorial, readers will learn how to download web pages, extract information from those pages, be able to store the extracted information and learn how to navigate across multiple pages of a website. A website has been created to assist readers in learning how to web scrape. The website contains a series of examples that look at how to scrape a single web page, and how to scrape multiple webpages. Each example is accompanied by a video describing the process of web scraping and an example R script.Accompanying exercises are also provided to help readers practice their knowledge and skills. Abstract Word Count: 200