A systematic approach to institutional analysis: Applying Crawford and Ostrom's grammar

In 1995, Crawford and Ostrom proposed a grammatical syntax for examining institutional statements (i.e., rules, norms, and strategies) as part of the institutional analysis and development framework. This article constitutes the first attempt at applying the grammatical syntax to code institutional statements using two pieces of U.S. legislation. The authors illustrate how the grammatical syntax can serve as a basis for collecting, presenting, and analyzing data in a way that is reliable and conveys valid and substantive meaning for the researcher. The article concludes by describing some implementation challenges and ideas for future theoretical and field research. © 2010 University of Utah.

Dissecting Policy Designs: An Application of the Institutional Grammar Tool

An enduring challenge for the policy and political sciences is valid and reliable depiction of policy designs. One emerging approach for dissecting policy designs is the application of Sue Crawford and Elinor Ostrom's institutional grammar tool. The grammar tool offers a method to identify, systematically, the core elements that comprise policies, including target audiences, expected patterns of behavior, and formal modes of sanctioning for noncompliance. This article provides three contributions to the study of policy designs by developing and applying the institutional grammar tool. First, we provide revised guidelines for applying the institutional grammar tool to the study of policy design. Second, an additional component to the grammar, called the oBject, is introduced. Third, we apply the modified grammar tool to four policies that shape Colorado State Aquaculture to demonstrate its effectiveness and utility in illuminating institutional linkages across levels of analysis. The conclusion summarizes the contributions of the article as well as points to future research and applications of the institutional grammar tool. © 2011 Policy Studies Organization.

Using the institutional grammar tool to understand regulatory compliance: The case of Colorado aquaculture

What is the relationship between the design of regulations and levels of individual compliance? To answer this question, Crawford and Ostrom's institutional grammar tool is used to deconstruct regulations governing the aquaculture industry in Colorado, USA. Compliance with the deconstructed regulatory components is then assessed based on the perceptions of the appropriateness of the regulations, involvement in designing the regulations, and intrinsic and extrinsic motivations. The findings suggest that levels of compliance with regulations vary across and within individuals regarding various aspects of the regulatory components. As expected, the level of compliance is affected by the perceived appropriateness of regulations, participation in designing the regulations, and feelings of guilt and fear of social disapproval. Furthermore, there is a strong degree of interdependence among the written components, as identified by the institutional grammar tool, in affecting compliance levels. The paper contributes to the regulation and compliance literature by illustrating the utility of the institutional grammar tool in understanding regulatory content, applying a new Q-Sort technique for measuring individual levels of compliance, and providing a rare exploration into feelings of guilt and fear outside of the laboratory setting. © 2012 Blackwell Publishing Asia Pty Ltd.

Computer vision tools for low-cost and noninvasive measurement of autism-related behaviors in infants.

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated which promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests that behavioral signs can be observed late in the first year of life. Many of these studies involve extensive frame-by-frame video observation and analysis of a child's natural behavior. Although nonintrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are burdensome for clinical and large population research purposes. This work is a first milestone in a long-term project on non-invasive early observation of children in order to aid in risk detection and research of neurodevelopmental disorders. We focus on providing low-cost computer vision tools to measure and identify ASD behavioral signs based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure responses to general ASD risk assessment tasks and activities outlined by the AOSI which assess visual attention by tracking facial features. We show results, including comparisons with expert and nonexpert clinicians, which demonstrate that the proposed computer vision tools can capture critical behavioral observations and potentially augment the clinician's behavioral observations obtained from real in-clinic assessments.

Computer vision tools for the non-invasive assessment of autism-related behavioral markers

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.

Participant, rater, and computer measures of coherence in posttraumatic stress disorder.

We examined the coherence of trauma memories in a trauma-exposed community sample of 30 adults with and 30 without posttraumatic stress disorder. The groups had similar categories of traumas and were matched on multiple factors that could affect the coherence of memories. We compared the transcribed oral trauma memories of participants with their most important and most positive memories. A comprehensive set of 28 measures of coherence including 3 ratings by the participants, 7 ratings by outside raters, and 18 computer-scored measures, provided a variety of approaches to defining and measuring coherence. A multivariate analysis of variance indicated differences in coherence among the trauma, important, and positive memories, but not between the diagnostic groups or their interaction with these memory types. Most differences were small in magnitude; in some cases, the trauma memories were more, rather than less, coherent than the control memories. Where differences existed, the results agreed with the existing literature, suggesting that factors other than the incoherence of trauma memories are most likely to be central to the maintenance of posttraumatic stress disorder and thus its treatment.