I took this course as an elective in the fall of 2005. As I wrote in my evaluation: "This course challenges you to think broadly and deeply about the institution of science and its connections with technology and the public. Readings are chosen to reflect the diversity of approaches that different writers have taken - especially with regard to the historical development of science and technology, the use of science to further other agendas, the larger cultural meanings and impacts of science that continue to evolve. The interdisciplinary and dynamic nature of science, technology, and public policy is ideally suited to a problem-based learning (PBL) unit. The PBL sessions allowed for individual research to be undertaken on a communally-decided topic. This meant that the angle you chose to investigate had to have practical relevance as well as intellectual interest – a good combination that was rigorous as well as participatory."
I particularly enjoy this kind of research, especially in a compressed time-frame (which is often the way it is in real life) so I was pleased with the outcome of the PBL unit, as shown below:
Community Based Disaster Management
A Briefing for the National Policy Analysis GroupPresenter: Jan Coe
Introduction
The mandate from the National Policy Analysis Group was to prepare a briefing on how to improve the science-policy connections with respect to extreme climate events. To help me focus on this task, I asked myself these questions: with our current state of knowledge, are we doing the best we can – in terms of preventing, preparing for, responding to, and recovering from disasters? How can research from the natural and social sciences assist in minimizing the traumatic effects of a natural hazard such as Hurricane Katrina?
Charles Meade and Megan Abbott from RAND were asking somewhat different questions when tasked with conducting an analysis of the full range of federal research and development (R&D) expenditures related to hazard loss reduction. The results of their study was meant to "contribute to the development of a policy framework that [would] help in future attempts to assess the 'payoffs' of various kinds of various kinds of R&D, including which efforts offered the greatest potential for reducing hazard loss" (Meade, 2003). The undertaking would have been fairly straightforward except for the authors' first surprising finding: that there is a lack of detailed data on losses from natural hazards. A large part of the report is spent on demonstrating why this is so and with the struggle to find a quantitative analysis method that fits what is known. They assert that the problem with this "missing metric" is that without it the cost effectiveness of various strategies cannot be determined, nor priorities set. Even the highest government entity set up to facilitate cooperation and coordination among all the various agencies dealing with natural hazard reduction and mitigation, the Subcommittee on Disaster Reduction or SDR (in the Office of Science & Technology Policy), was hamstrung in this regard.
Meade and Abbott found that in this information/policy vacuum, the most prominent hazard loss reduction R&D has been focused on known and demonstrable strategies, such as evacuations and short-term warning systems. While the goal of this research is to improve existing weather forecasting capabilities and is valuable, these kinds of improvements offer only modest hazard loss reductions. Their main findings were:
Explicit hazard loss reduction programs [mitigation] receive the least funding
The largest fraction of R&D spending goes to work on weather hazards and broadly related research on climatology, atmospheric science, and oceanography
Much of the R&D spending supports short-term prediction capabilities.
In addition, they make a fascinating loop into the question of the flawed nature of the linear model of basic vs. applied research when applied to "use-inspired" programs. The authors found that "the linear model of basic research to applied research to development places a disproportionate value on R&D related to weather forecasting systems, which are seen as the technological endpoint of a line of research efforts, a model of perfect linearity. In turn, other kinds of hazard loss reduction research may suffer from a perceived lack of direct (or linear) social benefit." (Meade, p.45). This is a theme I encountered many times when looking at the disaster-related programs that have been developed in the United States. We seem to be much drawn to technological solutions and complex modeling systems rather than the less glamorous mitigation tools such as land use planning, building codes enforcement, or lifestyle choices. The diagram below is their attempt to show that the social problem of hazard loss, "like all societal problems, frustrates a simple linear approach that links one clear concern to a logical, all-purpose solution. Thus, policymakers that are confronting hazard loss R&D decisions face a complicated, dynamic climate - one that thwarts any attempt to draw linear or direct connections between the problem (hazard losses) and the proposed solution (R&D that eliminates or drastically reduces such losses) (Meade, p. 54).
This diagram also shows that all these diverse factors point to the fact that policymakers face "less a geophysical problem than an inherently societal problem with a geophysical underpinning" (p 56).
As this particular insight from the report struck me, I decided to shift my focus to the social aspects of disasters, and in particular to investigating how the local populations in some countries appear to be organized more advantageously in terms of the overall ability of their citizens to respond to disaster planning and evacuations, for example. A report from Oxfam America titled Weathering the Storm: Lessons in Risk Reduction from Cuba strongly recommended the community-based civil defense system in Cuba as a model system in many respects. "It has tangible assets such as an early warning system, well-equipped rescue teams, and emergency stockpiles, as well as intangible assets such as community mobilization, solidarity, and a population that is 'disaster aware' and educated in the necessary actions to be taken in the event of a disaster" (Thompson, 2004). This contrasted, I felt, with the situation in the United States where, at least in the Katrina disaster, there was - for a time - chaos and lack of coordination even though there were substantial 'tangible assets' that could have been brought to bear. People were expecting and relying upon large governmental bureaucracies like FEMA to rescue them when local resources proved inadequate. So, is the multi-dimensional Cuban model one that can be replicated in other settings, or is it a unique product of its geography, culture, and strong, centralized government?
I decided to research the community based disaster management (CBDM) approach (which is utilized in Cuba) to see if I locate other examples, perhaps even within the United States. Project Impact, a FEMA mitigation program that ran from 1995 to 2001, was the closest example of CBDM that I could find. The Cuban model and Project Impact, will be investigated in detail in the Case Studies section below. Before that, however, some of the key terms and concepts relating to disaster management and CBDM will be reviewed.
My major project for the course was a study of the consensus conference as a form of participatory democracy. I compared consensus conferences from the United States, Australia, and the U.K. in an effort to discover how they stacked up against an "ideal" consensus conference framework that was modeled after Kitcher's "well-ordered science." ConsensusConferences
Science, Technology, and Public Policy
I took this course as an elective in the fall of 2005. As I wrote in my evaluation: "This course challenges you to think broadly and deeply about the institution of science and its connections with technology and the public. Readings are chosen to reflect the diversity of approaches that different writers have taken - especially with regard to the historical development of science and technology, the use of science to further other agendas, the larger cultural meanings and impacts of science that continue to evolve. The interdisciplinary and dynamic nature of science, technology, and public policy is ideally suited to a problem-based learning (PBL) unit. The PBL sessions allowed for individual research to be undertaken on a communally-decided topic. This meant that the angle you chose to investigate had to have practical relevance as well as intellectual interest – a good combination that was rigorous as well as participatory."
I particularly enjoy this kind of research, especially in a compressed time-frame (which is often the way it is in real life) so I was pleased with the outcome of the PBL unit, as shown below:
Community Based Disaster Management
A Briefing for the National Policy Analysis GroupPresenter: Jan CoeIntroduction
The mandate from the National Policy Analysis Group was to prepare a briefing on how to improve the science-policy connections with respect to extreme climate events. To help me focus on this task, I asked myself these questions: with our current state of knowledge, are we doing the best we can – in terms of preventing, preparing for, responding to, and recovering from disasters? How can research from the natural and social sciences assist in minimizing the traumatic effects of a natural hazard such as Hurricane Katrina?
Charles Meade and Megan Abbott from RAND were asking somewhat different questions when tasked with conducting an analysis of the full range of federal research and development (R&D) expenditures related to hazard loss reduction. The results of their study was meant to "contribute to the development of a policy framework that [would] help in future attempts to assess the 'payoffs' of various kinds of various kinds of R&D, including which efforts offered the greatest potential for reducing hazard loss" (Meade, 2003). The undertaking would have been fairly straightforward except for the authors' first surprising finding: that there is a lack of detailed data on losses from natural hazards. A large part of the report is spent on demonstrating why this is so and with the struggle to find a quantitative analysis method that fits what is known. They assert that the problem with this "missing metric" is that without it the cost effectiveness of various strategies cannot be determined, nor priorities set. Even the highest government entity set up to facilitate cooperation and coordination among all the various agencies dealing with natural hazard reduction and mitigation, the Subcommittee on Disaster Reduction or SDR (in the Office of Science & Technology Policy), was hamstrung in this regard.
Meade and Abbott found that in this information/policy vacuum, the most prominent hazard loss reduction R&D has been focused on known and demonstrable strategies, such as evacuations and short-term warning systems. While the goal of this research is to improve existing weather forecasting capabilities and is valuable, these kinds of improvements offer only modest hazard loss reductions. Their main findings were:
In addition, they make a fascinating loop into the question of the flawed nature of the linear model of basic vs. applied research when applied to "use-inspired" programs. The authors found that "the linear model of basic research to applied research to development places a disproportionate value on R&D related to weather forecasting systems, which are seen as the technological endpoint of a line of research efforts, a model of perfect linearity. In turn, other kinds of hazard loss reduction research may suffer from a perceived lack of direct (or linear) social benefit." (Meade, p.45). This is a theme I encountered many times when looking at the disaster-related programs that have been developed in the United States. We seem to be much drawn to technological solutions and complex modeling systems rather than the less glamorous mitigation tools such as land use planning, building codes enforcement, or lifestyle choices. The diagram below is their attempt to show that the social problem of hazard loss, "like all societal problems, frustrates a simple linear approach that links one clear concern to a logical, all-purpose solution. Thus, policymakers that are confronting hazard loss R&D decisions face a complicated, dynamic climate - one that thwarts any attempt to draw linear or direct connections between the problem (hazard losses) and the proposed solution (R&D that eliminates or drastically reduces such losses) (Meade, p. 54).
This diagram also shows that all these diverse factors point to the fact that policymakers face "less a geophysical problem than an inherently societal problem with a geophysical underpinning" (p 56).
As this particular insight from the report struck me, I decided to shift my focus to the social aspects of disasters, and in particular to investigating how the local populations in some countries appear to be organized more advantageously in terms of the overall ability of their citizens to respond to disaster planning and evacuations, for example. A report from Oxfam America titled Weathering the Storm: Lessons in Risk Reduction from Cuba strongly recommended the community-based civil defense system in Cuba as a model system in many respects. "It has tangible assets such as an early warning system, well-equipped rescue teams, and emergency stockpiles, as well as intangible assets such as community mobilization, solidarity, and a population that is 'disaster aware' and educated in the necessary actions to be taken in the event of a disaster" (Thompson, 2004). This contrasted, I felt, with the situation in the United States where, at least in the Katrina disaster, there was - for a time - chaos and lack of coordination even though there were substantial 'tangible assets' that could have been brought to bear. People were expecting and relying upon large governmental bureaucracies like FEMA to rescue them when local resources proved inadequate. So, is the multi-dimensional Cuban model one that can be replicated in other settings, or is it a unique product of its geography, culture, and strong, centralized government?
I decided to research the community based disaster management (CBDM) approach (which is utilized in Cuba) to see if I locate other examples, perhaps even within the United States. Project Impact, a FEMA mitigation program that ran from 1995 to 2001, was the closest example of CBDM that I could find. The Cuban model and Project Impact, will be investigated in detail in the Case Studies section below. Before that, however, some of the key terms and concepts relating to disaster management and CBDM will be reviewed.
To continue with the PBL unit, go to p. 2
My major project for the course was a study of the consensus conference as a form of participatory democracy. I compared consensus conferences from the United States, Australia, and the U.K. in an effort to discover how they stacked up against an "ideal" consensus conference framework that was modeled after Kitcher's "well-ordered science."
ConsensusConferences