Status Quo Approach Research Articles

Evaluation of carbon emission reduction effect of Cryptomeria japonica stand management in Yamagata Prefecture, Japan

Planted forests are in the utilisation phase in Japan, contributing to the increased use of timber and the realisation of carbon neutrality. We simulated and compared the carbon emission reduction effects of three forest management scenarios, including a no final cutting scenario at two geographical scales, in the context of a privately owned Cryptomeria japonica planted forest in Tsuruoka City, Yamagata Prefecture, Japan. We adopted two substitution approaches: the status quo approach and the dynamic approach in line with Japan’s nationally determined contribution. We used hypothetical stands over three rotation periods of 150 years at the stand level, and a harvest schedule of 120 years at the regional level. The harvesting scenarios based on the status quo substitution approach reduced carbon emissions more than the no final cutting scenario for current wood usage at the study site, although those based on the dynamic substitution approach reduced carbon emissions as much as the no final cutting scenario during the first 30 years. Sustainable timber production from forests may reduce carbon emissions as much as unharvested forests until 2050, indicating that the substitution effects of harvested wood products could have a significant impact on the climate change mitigation effect arising from timber.

Making concessions pay? Historical vs. potential tax revenues from Laos’s rubber sector

Under-taxation has been a prominent feature of the global land rush, figuring centrally in early concerns that transnational land deals constitute a new round of land grabbing rather than a source of productive investment. In the years since, however, under-taxation has been widely ignored in subsequent literature on state land concessions in the agri-plantation sector across the global South. To address this gap, this paper draws on ongoing research in Laos, where improved concession inventory efforts have helped stimulate a wide-ranging debate (both in and out of government) about the country’s still-opaque processes of concession taxation. We use the rubber sector to examine a pair of concession-taxation strategies that have been pursued to varying degrees both in Laos and more broadly: taxing land from the time it is alienated to a concessionaire (a land fee model), and taxing the resource itself – in this case rubber plantations – from the time they become productive (a royalty model). Using a quantitative-geographic approach enabled by Laos’s recently updated land concession inventory, we estimate potential tax revenues from rubber plantations under four taxation regimes that were deployed in various parts of the country over the last decade and a half: two of each type, with each type including higher and lower per-unit variants. Our analysis of the space of potential taxation implies significant opportunity costs inherent in the status-quo approach to taxation, which we discuss via the example of unaddressed need for concession-related compensation. Especially at the higher-end range, where taxation potentials total in the tens of millions of dollars per year, we find that Laos’s rubber-concession landscape has significant potential to help address this issue. To the degree that under-taxation is addressed in the future, however, new concession-tax revenues will increasingly be subject to spending demands from outside the rubber sector.

Conceptual and analytical approaches for modelling the developmental origins of inequality.

In many species, individuals that experience harsh conditions during development have poor health and fitness outcomes in adulthood, compared with peers that do not. These early-life contributions to inequality are often attributed to two classes of evolutionary hypotheses: Developmental Constraints (DC) models, which focus on the deleterious effects of low-quality early-life environments, and Predictive Adaptive Response (PAR) hypotheses, which emphasize the costs individuals incur when they make incorrect predictions about conditions in adulthood. Testing these hypotheses empirically is difficult for conceptual and analytical reasons. Here, we help resolve some of these difficulties by providing mathematical definitions for DC, PAR (particularly focusing on 'external' PAR) and related concepts. We propose a novel, quadratic regression-based statistical test derived from these definitions. Our simulations show that this approach markedly improves the ability to discriminate between DC and PAR hypotheses relative to the status quo approach, which uses interaction effects. Simulated data indicate that the interaction effects approach often conflates PAR with DC, while the quadratic regression approach yields high sensitivity and specificity for detecting PAR. Our results highlight the value of linking verbal and visual models to a formal mathematical treatment for understanding the developmental origins of inequitable adult outcomes. This article is part of the theme issue 'Evolutionary ecology of inequality'.

Israel in the Middle East: six strategies over the course of 75 years

ABSTRACT During its 75 years of existence, Israel’s strategies vis-à-vis its neighbours have alternated drastically in accordance with the vicissitudes in regional and global affairs: from reliance on force, to a status quo approach, to combining ‘land-for-peace’ approach while participating in ‘new wars’, to peace initiation, to unilateral action, to improved relations with the Arab world while trying to avoid the Palestinian issue. This article describes the evolution of these strategies, discusses their origin and underlying assumptions, and assesses their future implications.

Oman’s Foreign Policy and Its Mediating and Balancing Role in the Middle East

Oman, with its geographical location and ancient tradition, is a country that has succeeded in being a balancing factor, despite its distance from the central tensions of the Middle East and its ineffective appearance in regional politics. Especially during the 50-year reign of Sultan Qaboos that began in 1970, Oman was able to establish strategic relations with regional and global actors and adopted an exceptional foreign policy understanding in the Middle East during the Cold War period. After the death of Sultan Qaboos, Haitham bin Tariq took over the rule of the country as the new sultan of Oman. Under the new Sultan’s power, a pragmatic status quo approach has become the main pillar in the country’s foreign relations, as the traditional foreign policy understanding has been built on independence and moderation at a level that matches Oman’s will and capacity.
 This study presents a perspective on Oman’s foreign policy approach of Haitham bin Tariq, the Sultan of Oman, based on the analysis of traditional foreign policy framework and practices developed during the reign of Sultan Qaboos who was the architect of the country’s international relations. In this regard, this article examines in chronological order the continuities and ruptures of Omani foreign policy, which has been able to pursue effective policies, despite its low profile in the Middle East, by especially the mission it has assumed in the Gulf since Sultan Qaboos assumed power in 1970. The article also discusses the successful policies of Sultan Qaboos to remain moderate under all conditions and preserve the status quo in the Gulf. The study discusses in detail the exceptional case of Oman in the region using process tracing.

Corporations as Private Regulators

The growing trend of corporations imposing restrictions on suppliers, contractors, and customers beyond the requirements of existing laws requires rethinking the nature and impact of corporations’ private regulatory power. This trend, which this Article refers to as “Corporations as Private Regulators” (CPR), represents a paradigmatic shift in how corporations participate in the making of public policies. This Article conceptualizes the corporate CPR power as the exercise of a right of refusal to deal with counterparties. This right of refusal could be theorized as a new form of property right, whose allocation has important implications for both rights and wealth. The Article further explores the possible legal responses to CPR under various approaches, including the status quo approach, the ad hoc approach, the antitrust approach, the general CPR law approach, the property approach, and the constitutional approach. Finally, the Article analyzes the advantages and disadvantages, as well as the theoretical and practical implications, of each approach. The insights garnered through these inquiries lay the foundation for systematically tackling the CPR power.

Genetic information, insurance and a pluralistic approach to justice

The use of genetic testing has prompted the question of whether insurance companies should be able to use predictive genetic test results (GTRs) in their risk classification of clients. While...

On measuring agreement with numerically bounded linguistic probability schemes: A re-analysis of data from Wintle, Fraser, Wills, Nicholson, and Fidler (2019).

Across a wide range of domains, experts make probabilistic judgments under conditions of uncertainty to support decision-making. These judgments are often conveyed using linguistic expressions (e.g., x is likely). Seeking to foster shared understanding of these expressions between senders and receivers, the US intelligence community implemented a communication standard that prescribes a set of probability terms and assigns each term an equivalent numerical probability range. In an earlier PLOS ONE article, [1] tested whether access to the standard improves shared understanding and also explored the efficacy of various enhanced presentation formats. Notably, they found that embedding numeric equivalents in text (e.g., x is likely [55–80%]) substantially outperformed the status-quo approach in terms of the percentage overlap between participants’ interpretations of linguistic probabilities (defined in terms of the numeric range equivalents they provided for each term) and the numeric ranges in the standard. These results have important prescriptive implications, yet Wintle et al.’s percentage overlap measure of agreement may be viewed as unfairly punitive because it penalizes individuals for being more precise than the stipulated guidelines even when the individuals’ interpretations fall perfectly within the stipulated ranges. Arguably, subjects’ within-range precision is a positive attribute and should not be penalized in scoring interpretive agreement. Accordingly, in the present article, we reanalyzed Wintle et al.’s data using an alternative measure of percentage overlap that does not penalize in-range precision. Using the alternative measure, we find that percentage overlap is substantially elevated across conditions. More importantly, however, the effects of presentation format and probability level are highly consistent with the original study. By removing the ambiguity caused by Wintle et al.’s unduly punitive measure of agreement, these findings buttress Wintle et al.’s original claim that the methods currently used by intelligence organizations are ineffective at coordinating the meaning of uncertainty expressions between intelligence producers and intelligence consumers. Future studies examining agreement between senders and receivers are also encouraged to reflect carefully on the most appropriate measures of agreement to employ in their experiments and to explicate the bases for their methodological choices.

Operationalizing ensemble models for scientific advice to fisheries management

AbstractThis paper explores the possibility of using the ensemble modelling paradigm to fully capture assessment uncertainty and improve the robustness of advice provision. We identify and discuss advantages and challenges of ensemble modelling approaches in the context of scientific advice. There are uncertainties associated with every phase in the stock assessment process: data collection, assessment model choice, model assumptions, interpretation of risk, up to the implementation of management advice. Additionally, the dynamics of fish populations are complex, and our incomplete understanding of those dynamics and limited observations of important mechanisms, necessitate that models are simpler than nature. The aim is for the model to capture enough of the dynamics to accurately estimate trends and abundance, and provide the basis for robust advice about sustainable harvests. The status quo approach to assessment modelling has been to identify the “best” model and generate advice from that model, mostly ignoring advice from other model configurations regardless of how closely they performed relative to the chosen model. We discuss and make suggestions about the utility of ensemble models, including revisions to the formal process of providing advice to management bodies, and recommend further research to evaluate potential gains in modelling and advice performance.

Regulation and Redistribution with Lives in the Balance

A central question in law and economics is whether non-tax legal rules should be designed solely to maximize efficiency or whether they also should account for concerns about the distribution of income. This question takes on particular importance in the context of cost-benefit analysis. Federal agencies apply cost-benefit analysis when writing regulations that generate multibillion dollar impacts on the US economy and profound effects on millions of Americans’ lives. In the past, agency cost-benefit analyses typically have ignored the income-distributive consequences of those regulations. That may soon change: On his first day in office, President Biden instructed his Office of Management and Budget to propose procedures for incorporating distributive considerations into cost-benefit analysis, thus bringing renewed relevance to a long-running law-and-economics debate. This article explores what it might mean in practice for agencies to incorporate distributive considerations into cost-benefit analysis. It uses, as a case study, a 2014 rule promulgated by the National Highway Traffic Safety Administration (NHTSA) requiring new motor vehicles to have rearview cameras that reduce the risk of backover crashes. As with most major federal regulations that impose large dollar costs, the principal benefit of the rear visibility rule is a reduction in premature mortality. Quantitative cost-benefit analysis typically translates mortality reductions into dollar terms based on the “value of a statistical life,” or VSL. Any distributive evaluation of the rule will depend critically on a parameter known as the “income elasticity of the VSL,” which reflects the relationship between an individual’s income and her willingness to pay for mortality risk reductions. Although agency cost-benefit analyses use the same VSL for all individuals regardless of income, the Department of Transportation—of which NHTSA is a part—has issued guidance on the income elasticity of the VSL for other purposes. When this article applies the Department of Transportation’s income-elasticity guidance in its distributive analysis, the rear visibility rule appears to be “regressive”: it generates net costs for lower-income groups and net benefits for higher-income groups. Rerunning the distributive analysis with equal dollar VSLs at all income levels, the rule appears to be “progressive”: lower-income individuals are the primary beneficiaries and higher-income individuals are the losers. The article goes on to explain why assumptions about the relationship between income and the VSL will have important implications for distributive analyses of other lifesaving regulations. The article then asks what agencies ought to do: should they incorporate distributive objectives into cost-benefit analysis by assigning greater weight to dollars in lower-income individuals’ hands, and should they assign different dollar VSLs to individuals with different incomes? The two questions are closely linked. Incorporating distributive objectives into cost-benefit analysis of lifesaving regulations while maintaining equal dollar VSLs for rich and poor will potentially produce perverse outcomes that—according to standard economic thinking—actually redistribute from poor to rich. After canvassing options, this article ultimately concludes that the status quo approach—equal weights for low-income and high-income individuals’ dollars, equal dollar VSLs for low-income and high-income individuals—makes practical sense in light of expressive concerns, informational burdens, and institutional constraints. The article ends by reflecting on the case study’s lessons for broader debates over legal system design, and it explains why the issues that arise in the rear visibility case study are likely to affect other efforts to redistribute through non-tax legal rules.

Observed progeny performance validates the benefit of mating genetically elite beef sires to dairy females

While several studies in cattle have confirmed the improved performance achievable from selection on total merit indexes, these studies have solely been confined to specific-purpose beef or dairy total merit indexes. Validation studies of total merit indexes used to select beef sires for use on dairy females are lacking. The objective here was to fill this void by quantifying the performance of beef × dairy progeny where the sire excels in either a total merit index encompassing calving performance and beef performance traits (dairy-beef index; DBI) or excels in a subindex based solely on calving performance (CLV); for comparative purposes, these beef × dairy progeny were also compared with dairy × dairy progeny. A total of 123,785 calving records from 101,773 dairy cows calving in 3,065 dairy herds were used; of these, 48,875 progeny also had carcass information. The beef sires were stratified into 5 equally sized groups based separately on their DBI or CLV. Linear and threshold mixed models were used to compare calving and carcass performance of all 3 sire genotypes. Of the 415 sires that ranked in the highest of the 5 strata on the CLV subindex, only 52% of them ranked in the highest stratum for the DBI. The percentage of primiparae requiring any assistance at calving was 2 to 3 percentage units greater for the higher DBI sires relative to both the higher CLV beef sires and the dairy sires (not ranked on anything); no difference existed in multiparae. The extent of calving difficulty in primiparae was, however, less in higher DBI beef sires relative to both the higher CLV beef sires and the dairy sires, although the differences were biologically small. Perinatal mortality was greatest in the beef sires relative to the dairy sires, but no difference existed between the high CLV or high DBI beef sires. No difference in progeny gestation length was evident between the high DBI or high CLV beef sires, although both were >2 d longer than progeny from dairy sires. The higher DBI sires produced progeny with heavier, more conformed carcasses relative to the progeny from both high CLV beef sires and dairy sires. No differences existed between the progeny of the beef sires ranked highly on the CLV versus those ranked highly on the DBI for the probability of achieving the specification for carcass weight (between 270 and 380 kg) or fat score; the higher DBI animals, however, had a 4 to 10% greater probability of achieving the minimum carcass conformation required. In all instances, the beef sires had a greater probability of achieving all specifications relative to the progeny from the dairy sires with the difference for conformation being particularly large. Results indicate that more balanced progeny can be generated using a DBI, helping meet the requirements of both dairy and beef producers. Ignoring market failure across sectors, using higher DBI sires could increase dairy herd profit by 3 to 5% over and above the status quo approach to selection in dairy (i.e., CLV subindex).

Sustainability in architectural design projects – a semiotic understanding

ABSTRACT The potential of semiotics to theorize and analyze the field of sustainable architecture is still largely unexplored. This paper uses a triadic structure for defining sustainable design signs and distinguishes two separate modes of sustainable design reasoning: namely deductive and abductive sustainable design reasoning. This theoretical framework is used to analyze two architectural projects submitted for an international design competition in Montreal, Canada. The architectural texts, considered in this paper the representamen of the signs, prove to be indicative of the mode of reasoning deployed. The analysis also reveals that the mode of reasoning used dictates the types of signs produced, the role designed-objects have in the signs, as well as the functional possibilities design elements perform in the project. The paper proposes that deductive sustainable design reasoning brings to a halt the process of semiosis – presenting a status-quo approach – and that abductive sustainable design reasoning allows semiosis ad infinitum – presenting a future driven outlook. Additionally, a gap appeared between the open form of critical judgement proposed for competitions and the conceptual fixation inherit in deductive sustainable design reasoning. This paper presents a theoretical contribution that provides new possibilities for researchers to model and analyze sustainability in design projects.

Moving from a ‘human-as-problem” to a ‘human-as-solution” cybersecurity mindset

Abstract Cybersecurity has gained prominence, with a number of widely publicised security incidents, hacking attacks and data breaches reaching the news over the last few years. The escalation in the numbers of cyber incidents shows no sign of abating, and it seems appropriate to take a look at the way cybersecurity is conceptualised and to consider whether there is a need for a mindset change. To consider this question, we applied a “problematization” approach to assess current conceptualisations of the cybersecurity problem by government, industry and hackers. Our analysis revealed that individual human actors, in a variety of roles, are generally considered to be “a problem”. We also discovered that deployed solutions primarily focus on preventing adverse events by building resistance: i.e. implementing new security layers and policies that control humans and constrain their problematic behaviours. In essence, this treats all humans in the system as if they might well be malicious actors, and the solutions are designed to prevent their ill-advised behaviours. Given the continuing incidences of data breaches and successful hacks, it seems wise to rethink the status quo approach, which we refer to as “Cybersecurity, Currently”. In particular, we suggest that there is a need to reconsider the core assumptions and characterisations of the well-intentioned human’s role in the cybersecurity socio-technical system. Treating everyone as a problem does not seem to work, given the current cyber security landscape. Benefiting from research in other fields, we propose a new mindset i.e. “Cybersecurity, Differently”. This approach rests on recognition of the fact that the problem is actually the high complexity, interconnectedness and emergent qualities of socio-technical systems. The “differently” mindset acknowledges the well-intentioned human’s ability to be an important contributor to organisational cybersecurity, as well as their potential to be “part of the solution” rather than “the problem”. In essence, this new approach initially treats all humans in the system as if they are well-intentioned. The focus is on enhancing factors that contribute to positive outcomes and resilience. We conclude by proposing a set of key principles and, with the help of a prototypical fictional organisation, consider how this mindset could enhance and improve cybersecurity across the socio-technical system.

Planning power systems in fragile and conflict-affected states

Novel approaches are necessary to accelerate the provision of reliable electric power in fragile and conflict-affected countries. Existing approaches to planning power system investment tend to ignore conflict-related risk and its serious consequences. Here, we propose a framework for identifying power system investment strategies in fragile and conflict-affected countries, and apply it to South Sudan. Our results show that investment strategies that explicitly consider the challenges posed by potential conflict may improve the reliability of electricity service over the status-quo approach. Our analysis suggests investing in a diverse mix of supply types in the medium term, and building a power system with redundancies or a higher share of local resources in the long term, to reduce vulnerability to conflict and socio-political fragility. Planning of electric power systems often does not consider the potential for, and possible effects of, conflict and socio-political strife. Here, using a case study of South Sudan, researchers develop and implement a framework for power system planning in fragile and conflict-affected states.

Implementing Regulatory Broad Consent Under the Revised Common Rule: Clarifying Key Points and the Need for Evidence.

The revised Common Rule includes a new option for the conduct of secondary research with identifiable data and biospecimens: regulatory broad consent. Motivated by concerns regarding autonomy and trust in the research enterprise, regulators had initially proposed broad consent in a manner that would have rendered it the exclusive approach to secondary research with all biospecimens, regardless of identifiability. Based on public comments from both researchers and patients concerned that this approach would hinder important medical advances, however, regulators decided to largely preserve the status quo approach to secondary research with biospecimens and data. The Final Rule therefore allows such research to proceed without specific informed consent in a number of circumstances, but it also offers regulatory broad consent as a new, optional pathway for secondary research with identifiable data and biospecimens. In this article, we describe the parameters of regulatory broad consent under the new rule, explain why researchers and research institutions are unlikely to utilize it, outline recommendations for regulatory broad consent issued by the Secretary's Advisory Committee on Human Research Protections (SACHRP), and sketch an empirical research agenda for the sorts of questions about regulatory broad consent that remain to be answered as the research community embarks on Final Rule implementation.

Alternative Juvenile Production Estimate (JPE) Forecast Approaches for Sacramento River Winter-Run Chinook Salmon

Sacramento River winter-run Chinook salmon are listed under the Endangered Species Act as Endangered and there are substantial efforts to estimate, predict, and limit mortalities at various stages of their life cycle. One such effort is the annual forecast of the number of juvenile winter-run entering the Sacramento-San Joaquin Delta. The natural-origin Juvenile Production Estimate (JPE) is defined as the number of winter-run juveniles produced from natural spawning areas that enter the Delta, and its forecast is used to determine the allowable level of winter-run incidental take at the state and federal pumping facilities located in the south Delta. Current monitoring programs in the Sacramento Basin do not allow for direct estimation of the JPE and thus various methods have been used to forecast this value annually. Here we describe three alternative methods for forecasting the natural-origin JPE. The methods range from the status quo approach (Method 1), which expresses the JPE forecast only as a point estimate, to two other methods that account for forecast uncertainty to various degrees. A comparison of JPE forecasts for 2018 across the three methods indicates that relative to Method 1, Methods 2 and 3 result in lower JPE forecasts, by 24 and 18 percent, respectively, primarily owing to lower forecasts of the fry-to-smolt transition and the smolt survival rate occurring downstream of Red Bluff Diversion Dam. Because post-hoc estimates of juvenile winter-run abundance at the entrance to the Delta do not currently exist, we are unable to evaluate forecast skill among the three methods.

Working Towards a Framework for Stock Evaluations in Data‐Limited Fisheries

AbstractData‐limited approaches to managing fisheries are widespread in regions where insufficient data prevent traditional stock assessments from determining stock status with sufficient certainty to be useful for management. Where severe data limitations persist, a catch‐only approach is commonly employed, such as in the U.S. Caribbean region. This approach, however, has not received the level of scrutiny required to determine the potential long‐term risks (e.g., probability of overfishing) to fish stocks. In this study, we present a framework for comparison and implementation of data‐limited methods, including the static Status Quo approach, which uses average catch landings. Candidate species for stock evaluation were identified through a data triage and included Yellowtail Snapper Ocyurus chrysurus (Puerto Rico), Queen Triggerfish Balistes vetula (St. Thomas and St. John), and Stoplight Parrotfish Sparisoma viride (St. Croix). Feasible data‐limited methods, based on data availability and quality, included empirical indicator approaches using relative abundance (i.e., catch per unit effort) or mean length. Results from the management strategy evaluation support the use of adaptive data‐limited methods, which incorporate feedback in contrast to the static Status Quo approach. The proposed framework can help guide the development of catch advice for dynamic fisheries management in data‐limited regions.

Other Costs, Other Markets: Modernizing Antitrust

Today’s antitrust law is characterized by stagnation and indeterminacy. The failure is so thorough that it is not clear that U.S. competition law actually leads to any outcomes that are defendable except at the most superficial level. Moreover, when enforcement does result in a desirable outcome, it not clear that it is the best outcome. The principal reason for this state of affairs is that antitrust scholars and courts cling to misguided goals and theories that have not evolved despite an avalanche of information now available that can modernize the discipline.This Article has two main sections that necessarily overlap. The first examines the three principal goals of antitrust — consumer surplus, allocative efficiency, and productive efficiency — and explains why they are imperfect, incomplete, and indeterminate guides for policy. The purpose of this section is not to express a nihilistic view of antitrust but to demonstrate that those who protect the status quo approach to antitrust stand on a wobbly foundation and to suggest that if the current rigidity in antitrust economics continues it will be at the expense of the relevancy of the discipline. It includes, sometimes by implication, proposals for improvement. The second section continues that basic theme but considers two areas in which growth is needed if antitrust is to remain relevant in the next fifty years. They may or may not be addressed but, if they are not, the legitimacy of antitrust economics and its application will surely be called into question. This material stresses the need, if there is to be a coherent antitrust policy, to broaden the scope of factors to consider when assessing the effectiveness of modern competition policy. The concluding section offers specific recommendations for the modernization of antitrust.

Because 'Yes' Actually Means 'No': A Personalized Prescriptive to Reactualize Informed Consent in Dispute Resolution

This paper proposes a radical departure from the status quo approach to securing a client’s informed consent about settlement options and refocuses informed consent practice back to what informed consent is about, the client. As it exists today, the status quo approach to securing a client’s informed consent about whether or not to use an alternative dispute resolution procedure to resolve the client’s case is inadequate. It thwarts a client’s right to exercise party self- determination and stymies a client’s ability to make informed justice choices. Lawyers, courts, ADR providers and neutrals routinely provide litigants with generic information about the structure and procedures of dispute resolution procedures that these professionals assume litigants need to make an informed decision about whether or not to litigate or to use alternative choices. Litigants, however, might find this information inadequate to support their personal decision making process. Furthermore, litigants often find this information presented in a way that is incomprehensible to the litigant’s way of processing information and making decisions. Conspicuously absent from this one-size-fits-all approach to informed consent is a more customized way to share information about the dispute resolution procedures that is tailored to the particular individual’s needs, values, and decision-making process. Despite this inadequate information, however, many litigants still give a reflexive assent to the generic recitation of information explaining dispute resolution procedures, believing that they have no real choice. Some litigants may not even realize that they have the autonomy to choose as part of their right to make decisions about their case. Still, other litigants may be hesitant to ask for additional information, not wanting to be viewed as “stupid.” Still, others may not fathom what information they might want or need to know in order to make an informed choice. Thus, when litigants agree to participate in or opt out of a dispute resolution procedure, their “yes” may mean “no.” The proposal culls from both the research on dispute resolution literacy and the innovations in the health care industry regarding informed consent and recommends a three part prescriptive. First, a database will be created that contains the universe of information that individual consumers of dispute resolution actually want to know when choosing their justice option. Second, from the broader database, each client will be able to develop his or her own customized personal profile of informational needs. The personal profile will titrate the information from the broader database and provide the client with information tailored to each client’s informational, decision-making and personal preferences. Third, lawyers and dispute resolution professionals will be educated about how to use the client’s personal profile to tailor the professional-client conversation to include relevant information to the client about the dispute resolution options being considered. The goal is to fortify clients with the information about dispute resolution procedures commensurate with the client’s informational needs, decision making process and personal values so that the client will finally be able to give their meaningful informed consent to their justice option choice.

Neurosurgeon

The computation for today's intelligent personal assistants such as Apple Siri, Google Now, and Microsoft Cortana, is performed in the cloud. This cloud-only approach requires significant amounts of data to be sent to the cloud over the wireless network and puts significant computational pressure on the datacenter. However, as the computational resources in mobile devices become more powerful and energy efficient, questions arise as to whether this cloud-only processing is desirable moving forward, and what are the implications of pushing some or all of this compute to the mobile devices on the edge. In this paper, we examine the status quo approach of cloud-only processing and investigate computation partitioning strategies that effectively leverage both the cycles in the cloud and on the mobile device to achieve low latency, low energy consumption, and high datacenter throughput for this class of intelligent applications. Our study uses 8 intelligent applications spanning computer vision, speech, and natural language domains, all employing state-of-the-art Deep Neural Networks (DNNs) as the core machine learning technique. We find that given the characteristics of DNN algorithms, a fine-grained, layer-level computation partitioning strategy based on the data and computation variations of each layer within a DNN has significant latency and energy advantages over the status quo approach. Using this insight, we design Neurosurgeon, a lightweight scheduler to automatically partition DNN computation between mobile devices and datacenters at the granularity of neural network layers. Neurosurgeon does not require per-application profiling. It adapts to various DNN architectures, hardware platforms, wireless networks, and server load levels, intelligently partitioning computation for best latency or best mobile energy. We evaluate Neurosurgeon on a state-of-the-art mobile development platform and show that it improves end-to-end latency by 3.1X on average and up to 40.7X, reduces mobile energy consumption by 59.5% on average and up to 94.7%, and improves datacenter throughput by 1.5X on average and up to 6.7X.