Comparing Computational Power

It is common practice to compare the computational power ofdifferent models of computation. For example, the recursivefunctions are strictly more powerful than the primitive recursivefunctions, because the latter are a proper subset of the former(which includes Ackermann's function). Side-by-side with this"containment" method of measuring power, it is also standardto base comparisons on "simulation". For example, one says thatthe (untyped) lambda calculus is as powerful—computationallyspeaking—as the partial recursive functions, because thelambda calculus can simulate all partial recursive functionsby encoding the natural numbers as Church numerals. The problem is that unbridled use of these two distinct waysof comparing power allows one to show that some computationalmodels (sets of partial functions) are strictly stronger thanthemselves! We argue that a better definition is that modelA is strictly stronger than B if A can simulate B via some encoding,whereas B cannot simulate A under any encoding. We show thatwith this definition, too, the recursive functions are strictlystronger than the primitive recursive. We also prove that therecursive functions, partial recursive functions, and Turingmachines are "complete", in the sense that no injective encodingcan make them equivalent to any "hypercomputational" model.¹     

Vulnerable Populations in Research: The Case of the Seriously Ill

This paper advances a new criterion of a vulnerable population in research. According to this criterion, there are consent-based and fairness-based reasons for calling a group vulnerable. The criterion is then applied to the case of people with serious illnesses. It is argued that people with serious illnesses meet this criterion for reasons related to consent. Seriously ill people have a susceptibility to “enticing offers” that hold out the prospect of removing or alleviating illness, and this susceptibility reduces their ability to safeguard their own interests. This explains the inclusion of people with serious illnesses in the Belmont Report’s list of populations needing special protections, and supports the claim that vulnerability is the rule, rather than the exception, in biomedical research.     

Community Psychology at the Crossroads: Prospects for Interdisciplinary Research

Effective engagement in interdisciplinary work is critical if community psychology is to achieve its promise as a field of ecological inquiry and social action. The purpose of this paper and special issue is to help make the benefits of interdisciplinary community research clearer and to identify and begin to address its challenges. Although some areas of psychology (e.g., biological, cognitive and health) have made substantial interdisciplinary strides in recent decades, progress in community psychology (and related areas) is more modest. In this article we explore the prospects for expanding and improving interdisciplinary community research. Challenges include designs, measures, and analytical frameworks that integrate multiple levels of analysis from individuals through families, organizations, and communities to policy jurisdictions, and the complexities involved in simultaneously bringing together multiple disciplinary collaborators and community partners. Challenges to interdisciplinary collaboration common to all disciplines include the disciplinary nature of academic culture and reward structures, limited funding for interdisciplinary work and uncertainties related to professional identity and marketability. Overcoming these challenges requires a synergy among facilitative factors at the levels of the interdisciplinary project team (e.g., the framing question; embedded relationships; leadership), the investigators (e.g., commitment to new learning; time to invest), and the external context (e.g., physical, administrative, economic and intellectual resources and support for interdisciplinary work). We conclude by identifying several exemplars of effective interdisciplinary collaborations and concrete steps our field can take to enhance our development as a vibrant community-based, multilevel discipline increasingly devoted to interdisciplinary inquiry and action.     

Developing a Partnership Model for Cancer Screening with Community-Based Organizations: The ACCESS Breast Cancer Education and Outreach Project

There is growing enthusiasm for community-academic partnerships to promote health in underserved communities. Drawing upon resources available at a comprehensive cancer center, we developed the ACCESS program to guide community based organizations through a flexible program planning process. Over a three-year period, ACCESS partnered with 67 agencies serving various medically underserved populations. Organizations included hospitals, parishes, senior centers, harm reduction programs, and recreational facilities. Program outcomes at the organizational level were quantified in terms of introduction of new cancer information, referral or screening programs, as well as organizational capacity building. ACCESS represents a viable model for promoting partnership to transfer behavioral health programs and adapt interventions for new audiences. Plans to further evaluate and enhance this model to promote cancer screening efforts are discussed. We argue that, ultimately, formation and development of community partnerships need to be understood as a fundamental area of practice that must be systematically integrated into the mission of major academic medical institutions in every area of public health.     

The Making of an Interdisciplinary Partnership: The Case of the Chicago Food System Collaborative

Interdisciplinary partnerships foster innovation to address pressing social problems. This paper describes an interdisciplinary partnership called the Chicago Food System Collaborative (CFSC) composed of a team of partners from four academic institutions and three community-based organizations representing a total of eight disciplines that included: community development and community organizing, community psychology, geography, nursing, nutrition, public health, sociology, and urban planning and policy. Partners came together to address the issue of access to healthy foods and nutrition in a working class African American neighborhood. We analyze and discuss the core principles that guided the partnership and its impact across three dimensions: understanding through interdisciplinary action research, building capacity, and facilitating innovations in practices and policies. Despite the challenges of interdisciplinary partnerships, the potential benefits and impact of such efforts reflect their value as a comprehensive approach to addressing complex social problems.     

Building Interdisciplinary/Intersectoral Research Partnerships for Community-Based Mental Health Research with Older Minority Adults

Community-based research often brings investigators from different disciplinary backgrounds together with community representatives to conduct research on topics of mutual concern. This paper describes a case example that illustrates an interdisciplinary/intersectoral study of depression and barriers to mental health care among older adults and illustrate the factors central to implementing a successful research partnership. It will address the following conditions that facilitate and challenge interdisciplinary/intersectoral research: (1) achieving commonality of purpose in study design and research and referral approaches; (2) ensuring the ability to develop, field-test and implement psychometrically rigorous and culturally and qualitatively appropriate instruments; (3) building effective management structures for interdisciplinary/intersectoral research partnerships; and (4) identifying, training and supporting qualified researchers to carry out a mental health study with older ethnically diverse adults. The paper concludes with strengths and limitations of the approach.     

The definition of adequate care in externally sponsored clinical trials: The terminological controversy about the concept “standard of care”

The treatment of the control group in externally sponsored clinical trials is the issue of one of the most heated debates in international research ethics. The paradigmatic cases are the mother-to-child HIV-transmission trials that took place in 16 developing countries in 1997, where the control group received a placebo while proven treatment was available in industrialized countries. From this circumstance results the controversy as to whether the sponsor and researchers of externally sponsored trials have to supply a treatment that is usually not available in the host country. From the beginning of the debate the controversial level of treatment has been called “standard of care”. However, besides the disagreement about the quality of the care that has to be supplied, there is as yet no widely accepted clear meaning of this concept. This article examines the fundamental ambiguity of the term and its formal function as an ethical criterion including suggestions on its further use. This paper was presented at the 6th International Bioethics Conference on the subject of ‘The Responsible Conduct of Basic and Clinical Research’, held in Warsaw, Poland, 3–4 June 2005.     

A model of plausibility

Plausibility has been implicated as playing a critical role in many cognitive phenomena from comprehension to problem solving. Yet, across cognitive science, plausibility is usually treated as an operationalized variable or metric rather than being explained or studied in itself. This article describes a new cognitive model of plausibility, the Plausibility Analysis Model (PAM), which is aimed at modeling human plausibility judgment. This model uses commonsense knowledge of concept-coherence to determine the degree of plausibility of a target scenario. In essence, a highly plausible scenario is one that fits prior knowledge well: with many different sources of corroboration, without complexity of explanation, and with minimal conjecture. A detailed simulation of empirical plausibility findings is reported, which shows a close correspondence between the model and human judgments. In addition, a sensitivity analysis demonstrates that PAM is robust in its operations.     

Uncertainty about the rest of the sentence

A word-by-word human sentence processing complexity metric is presented. This metric formalizes the intuition that comprehenders have more trouble on words contributing larger amounts of information about the syntactic structure of the sentence as a whole. The formalization is in terms of the conditional entropy of grammatical continuations, given the words that have been heard so far. To calculate the predictions of this metric, Wilson and Carroll's (1954) original entropy reduction idea is extended to infinite languages. This is demonstrated with a mildly context-sensitive language that includes relative clauses formed on a variety of grammatical relations across the Accessibility Hierarchy of Keenan and Comrie (1977). Predictions are derived that correlate significantly with repetition accuracy results obtained in a sentence-memory experiment (Keenan & Hawkins, 1987).