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From the 1890s onwards, social reformers, volunteer lawyers, and politicians increasingly came to see access to affordable or free legal advice as a critical part of helping working-class people uphold their rights with landlords, employers, and retailers - and, from the 1940s, with the welfare state. Whilst a state scheme was launched in 1949, it was never fully implemented and help from a lawyer remained out of the reach of many people. Lawyers for the poor is the first full-length study of the development of voluntary action and mutual schemes to make the law more accessible, and the pressure put on the legal profession and governments to bring in further reforms. It offers new insights of the role of access to the law in shaping ideas about citizenship and civil rights in the twentieth century.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multi-scale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level provides the foundation needed to support this evolution.

In recent years, many companies have emphasized adjusted-GAAP earnings numbers in their quarterly press releases. While managers use different names to describe these nonstandard earnings metrics, the financial press frequently refers to them as \"pro forma\" earnings. Managers and other advocates of pro forma reporting argue that these disclosures provide a clearer picture of companies' core earnings. On the other hand, regulators, policymakers, and the financial press often allege that managers' pro forma earnings disclosures are opportunistic attempts to mislead investors. Recent evidence suggests that while many pro forma earnings disclosures are altruistically motivated, some may represent managers' attempts to portray overly optimistic financial performance. If this is the case, then less wealthy, less sophisticated, individual investors are arguably the most at risk of being misled. Consequently, this study investigates who trades on pro forma earnings information. Our intraday investigation of transactions around earnings announcements containing pro forma earnings information reveals that less sophisticated investors' announcement-period abnormal trading is significantly positively associated with the magnitude and direction of the earnings surprise based on pro forma earnings. In contrast, we find no association between sophisticated investors' trading and manager-reported pro forma information. Overall, our analyses and numerous robustness tests suggest that the segment of the market that relies on pro forma earnings information is populated predominantly by less sophisticated individual investors. This evidence is particularly relevant to standard-setters and regulators given that Section 401(b) of the Sarbanes-Oxley Act of 2002 and subsequent SEC regulations are specifically designed to protect ordinary investors from misleading pro forma information.

This study presents the results of an experiment that examines how two underlying characteristics of pro forma earnings announcements, pro forma emphasis and the presence of a quantitative reconciliation, influence nonprofessional investors' and analysts' reliance on pro forma disclosures. The results indicate that the emphasis management places on pro forma earnings, not the mere presence of pro forma earnings, influences nonprofessional investors' judgments and decisions, but that this influence is mitigated by the presence of a quantitative reconciliation. Further analysis reveals that the influence of pro forma emphasis on nonprofessional investors' judgments and decisions seems to be the result of an unintentional cognitive effect as opposed to the perceived informativeness of the earnings Figure emphasized by management. Analysts' judgments and decisions were also affected by the presence of reconciliation, but in the opposite direction to those of nonprofessional investors. Specifically, the presence of a quantitative reconciliation led analysts to view pro forma earnings as more reliable, increasing their reliance on the pro forma disclosure in judging the earnings performance of the firm.

This study examines the incremental information in loss firms' non-GAAP earnings disclosures relative to GAAP earnings. Using a large sample obtained through textual analysis and hand-collection, we posit and find that loss firms' non-GAAP earnings exclusions offset the low informativeness of GAAP losses for forecasting and valuation. Loss firms' non-GAAP earnings are highly predictive of future performance and are valued by investors, while the expenses excluded from GAAP earnings are not. Additional tests suggest that loss firms disclosing non-GAAP profits have significantly better future performance than GAAP-only loss firms and are not overvalued by investors. Comparing non-GAAP earnings of profitable firms to those of loss firms, we find that loss firms' non-GAAP metrics are significantly more predictive and less strategic. We conclude that non-GAAP earnings disclosures are particularly informative about loss firms and help investors disaggregate losses into components that have differential implications for forecasting and valuation.

We empirically examine the effects of intensified scrutiny over non-GAAP reporting on the quality of non-GAAP earnings exclusions. We find that, on average, exclusions are of higher quality (i.e., more transitory) following intervention by the Securities and Exchange Commission (SEC) into non-GAAP reporting. We further find that firms that stopped releasing non-GAAP earnings numbers after the SEC intervention had lower quality exclusions in the pre-intervention period. These results are consistent with the SEC's objectives of improving the quality of non-GAAP earnings figures. However, when we decompose total exclusions into special items and other exclusions, we find evidence that the quality of special items has decreased in the post-intervention period, which suggests that managers adapted to the new disclosure environment by shifting more recurring expenses into special items. This suggests that there may be unintended consequences arising from the heightened scrutiny over non-GAAP reporting.

This paper presents an experiment that examines the effect of pro forma earnings disclosures on the judgments of analysts (i.e., more sophisticated investors) and nonprofessional (i.e., less sophisticated) investors. In the experiment, participants developed stock price assessments after reviewing background financial information and a current earnings announcement for a company. The earnings announcement was manipulated to report only GAAP earnings in one condition and both pro forma and GAAP earnings in the other condition. Consistent with empirical evidence, the pro forma earnings in our experiment exceeded GAAP earnings. The results indicate that nonprofessional investors who received an earnings announcement that contained both pro forma and GAAP disclosures assessed a higher stock price than did nonprofessionals who received an announcement containing only GAAP disclosures. Financial analysts' stock price judgments were not affected by the pro forma disclosures. Follow-up analyses suggest that analysts and nonprofessional investors used different valuation models and information processing. Analysts used well-defined valuation models, based on either earnings-multiples or cash flows, while the nonprofessional investors were more likely to use simpler, heuristic-based valuation models. The pro forma disclosure did not cause nonprofessional investors to assess a higher earnings number for determining a stock price, but rather caused nonprofessionals to perceive the earnings announcement as more favorable, which in turn caused them to convert earnings or some other performance metric into a higher stock price. This effect appears to be due to unintentional cognitive effects, rather than nonprofessionals relying on pro forma earnings information because they perceived it to be informative.

This study examines how key market participants—managers and analysts—responded to SFAS 123R’s controversial requirement that firms recognize stock-based compensation expense. Despite mandated recognition of the expense, some firms’ managers exclude it from pro forma earnings and some firms’ analysts exclude it from Street earnings. We find evidence consistent with managers opportunistically excluding the expense to increase earnings, smooth earnings, and meet earnings benchmarks but no evidence that these exclusions result in an earnings measure that better predicts future firm performance. In contrast, we find that analysts exclude the expense from earnings forecasts when exclusion increases earnings’ predictive ability for future performance and that opportunism generally does not explain exclusion by analysts incremental to exclusion by managers. Thus our findings indicate that opportunism is the primary explanation for exclusion of the expense from pro forma earnings and predictive ability is the primary explanation for exclusion from Street earnings. Our findings suggest the controversy surrounding the recognition of stock-based compensation expense may be attributable to cross-sectional variation in the relevance of the expense for equity valuation, as well as to differing incentives of market participants.

•Age-, reading-level-matched and developmental connectivity analyses in children.•Effective connectivity was assessed in children with and without dyslexia.•Connectivity was also assessed in development of children with and without dyslexia.•Feedforward connections from the visual word form area (VWFA) increased with age.•Connectivity from the inferior parietal lobule to the VWFA was altered in dyslexia. Altered brain connectivity between regions of the reading network has been associated with reading difficulties. However, it remains unclear whether connectivity differences between children with dyslexia (DYS) and those with typical reading skills (TR) are specific to reading impairments or to reading experience. In this functional MRI study, 132 children (M = 10.06 y, SD = 1.46) performed a phonological lexical decision task. We aimed to disentangle (1) disorder-specific from (2) experience-related differences in effective connectivity and to (3) characterize the development of DYS and TR. We applied dynamic causal modeling to age-matched (ndys = 25, nTR = 35) and reading-level-matched (ndys = 25, nTR = 22) groups. Developmental effects were assessed in beginning and advanced readers (TR: nbeg = 48, nadv = 35, DYS: nbeg = 24, nadv = 25). We show that altered feedback connectivity between the inferior parietal lobule and the visual word form area (VWFA) during print processing can be specifically attributed to reading impairments, because these alterations were found in DYS compared to both the age-matched and reading-level-matched TR. In contrast, feedforward connectivity from the VWFA to parietal and frontal regions characterized experience in TR and increased with age and reading skill. These directed connectivity findings pinpoint disorder-specific and experience-dependent alterations in the brain's reading network.

Appreciating spatial scale is crucial for our understanding of the sociospatial context. Multiscale measures of population have been developed in the segregation and neighborhood effects literatures, which have acknowledged the role of a variety of spatial contexts for individual outcomes and intergroup contacts. Although existing studies dealing with sociospatial inequalities increasingly explore the effects of spatial scale, there has been little systematic evidence on how exposure to sociospatial contexts changes across urban space, both within and between cities. This article presents a multiscale approach to measuring potential exposure to others. Using individual-level register data for the full population of The Netherlands and an exceptionally detailed multiscalar framework of bespoke neighborhoods at 101 spatial scales, we measured the share of non-Western ethnic minorities for three Dutch cities with different urban forms. We created individual and cumulative distance profiles of ethnic exposure, mapped ethnic exposure surfaces, and applied entropy as a measure of scalar variation to compare potential exposure to others in different locations both within and between cities. The multiscale approach can be implemented for examining a variety of social processes, notably segregation and neighborhood effects.