Social Movement Transformation and Pre-movement Factor-effect: a Preliminary Inquiry

A source of social movement transformation which has been relatively neglected by researchers involves the effect of factors in the pre-movement environment which reemerge sporadically throughout the careers of social movements. Their reemergence may account for the direction of the transformation process and, specifically, for the differential transformations which characterize some movements at various points in their careers. A case study illustrating this effect is presented, followed by a more general consideration of when this phenomenon may be expected to occur and what movement-related factors facilitate its effects.     

Accident Epidemiology and the U.S. Chemical Industry: Accident History and Worst-Case Data from RMP*Info

This article reports on the data collected on one of the most ambitious government-sponsored environmental data acquisition projects of all time, the Risk Management Plan (RMP) data collected under section 112(r) of the Clean Air Act Amendments of 1990. This RMP Rule 112(r) was triggered by the Bhopal accident in 1984 and led to the requirement that each qualifying facility develop and file with the U.S. Environmental Protection Agency a Risk Management Plan (RMP) as well as accident history data for the five-year period preceding the filing of the RMP. These data were collected in 1999-2001 on more than 15,000 facilities in the United States that store or use listed toxic or flammable chemicals believed to be a hazard to the environment or to human health of facility employees or off-site residents of host communities. The resulting database, RMP*Info, has become a key resource for regulators and researchers concerned with the frequency and severity of accidents, and the underlying facility-specific factors that are statistically associated with accident and injury rates. This article analyzes which facilities actually filed under the Rule and presents results on accident frequencies and severities available from the RMP*Info database. This article also presents summaries of related results from RMP*Info on Offsite Consequence Analysis (OCA), an analytical estimate of the potential consequences of hypothetical worst-case and alternative accidental releases on the public and environment around the facility. The OCA data have become a key input in the evaluation of site security assessment and mitigation policies for both government planners as well as facility managers and their insurers. Following the survey of the RMP*Info data, we discuss the rich set of policy decisions that may be informed by research based on these data.     

Short-term, population-based forecasting in the public sector

There has recently been a tremendous expansion of the range of problems to which the demographic perspective is applied. Development of a new population-based method to solve the problem of forecasting income assistance caseloads for the state of Washington represents yet another effort in which the demographic perspective helps solve two major public-policy problems: (1) providing accurate and useful forecasts of caseloads, and (2) creating a dynamic model with which to analyze alternative policy proposals. When forecasting or examining the caseload history, it is also common to look at these caseload levels as a time-series. A caseload grows and shrinks as time passes because new members enter the caseload from a population of potential clients while other members exit the caseload. Population-based forecasting, as reported here, is really quite a novel approach to forecasting public assistance caseloads. In most situations, simple extrapolations of past trends or econometric time-series models are used. Characteristics associated with entries and exits can be used to develop dynamic models of current and future caseload changes. For budgeting purposes, these models can be readily translated into average annual caseload levels and can be directly used to examine policy alternatives and programmatic options. Entry and exit rates and volumes can be related to historical, current, and anticipated changes in economic, social, and programmatic conditions to develop models of caseload behavior, and ultimately, forecasts of caseload levels that are used for budget development.     

Abortion on demand in France? a five-year trial for the "time limit solution"

France's Assemblee Nationale and Senate passed a "time-limit solution" abortion law on December 20, 1974. Abortion is permitted on demand by a physician in a hospital during the 1st 10 weeks of pregnancy. The tone of the law stresses the concept of respect for life and suggests the undesirability of abortion. The developing child is recognized as a human being whose life has begun. The woman herself is responsible for her distress is sufficient to warrant abortion. Further provisions insure that the woman is as well-informed as possible concerning medical risks and possibilities of adoption and requires consultation with an information, consultation, or family counseling service, family planning center, or other social service organization. French scientists, physicians, magistrates, and religious leaders opposed the permissive law. The victory of the proabortionists was created by the political decision of the Socialists and Communists to impose party discipline and to require a unanimous vote for liberalization.     

Abortion: rights or technicalities? A comparison of Roe v. Wade with the abortion decision of the German Federal Constitutional Court

A comparison of the difference in approach, philosophy, and percepti on of social implications of abortion in the United States and Germany is examined by contrasting the Roe v. Wade decision of the U.S. Supreme Court with the abortion decision of the German Federal Constitutional Court. Roe v. Wade effectively established abortion on demand prior to "viability" (approximately 6 months) and makes it difficult to prevent it for any reason at any time prior to live birth. When the West German Federal Diet passed the Fifth Law for the Reform of the Penal Code which allowed abortion on request up to 12 weeks of conception and for reasons of maternal health up to 22 weeks, the Constitutional Court declared it null and void 8 months later. The 2 courts reached their decisions for quite different reasons. In the U.S. "Jane Roe" was a real, though anonymous, woman. Other real persons had been trying to overturn abortion statutues in various states. The German court acted on a petition brought by 193 members of the Federal Diet and 4 of the states. It was thus, under the German system, obligated to decide the constitutionality of the revisions in abortion legislation and the decision returned the question to the legislative body. The fundamental difference between the German and the American approach is the "right to life." In America the conflict is between the mother's "right to privacy" and the compelling interest of the state to protect the right to life. At no point does the U.S. Supreme Court consider whether the unborn has rights but only whether they constitute a value the protection of which is a legitimate state interest. In Germany, by contrast, the Federal Constitution explicitly establishes the right to life as a subjective human right; the state not only has no right to take life but acknowledges that this right belongs to the human being himself. The U.S. court reasoned that the unborn have been protected "only" for the last century while the German court stated the right has "already" been recognized for a century. The U.S. Court made no mention of the wider social implications of the decision except for a few brief references; the German court's major consideration was the social implication of the law. An appendix with 6 refs. give a translation of the German court's decision.     

The effect of density on the level of bias in the network autocorrelation model

Researchers interested in the effects of social network ties on behavior are increasingly turning to the network autocorrelation model, which allows for the simultaneous computation of individual-level and network-level effects. Earlier research, however, had pointed to the possibility that the maximum likelihood estimates used to compute the network autocorrelation model yielded negatively biased parameter estimates. In this paper we use simulations to examine whether – and the conditions under which – a negative bias exists. We show that the network parameter estimate ρ is negatively biased under nearly all conditions, and that this bias becomes more severe at higher levels of both ρ and network density. We conclude by discussing the implications of these findings for researchers planning to use the network autocorrelation model.