The Independence of Aptitudes,Interests, and Career Beliefs

The importance of client beliefs in career counseling depends on their ability to add unique information about the client over and above that contributed by aptitudes and interests. The Career Beliefs Inventory was administered to 200 Australian students in grade 10 together with measures of Holland's RIASEC interest themes and scholastic aptitudes. The correlations between scales from the three domains showed clearly that beliefs made a contribution distinct from that provided by aptitudes and interests. Even though the results may reflect possible sampling or method variance, career beliefs in this sample added unique information to that traditionally used in career counseling.     

QUESTION WORDING AND PARTISANSHIP: CHANGE AND CONTINUITY IN PARTY LOYALTIES DURING THE 1992 ELECTION CAMPAIGN

Gallup macropartisanship varies more over time than aggregatemeasures of partisanship employing the standard Michigan SurveyResearch Center (SRC) party identification measure, but previousanalyses do not provide direct evidence about why Gallup macropartisanshipis more variable. Although these differences could result fromthe short-term focus of the Gallup party affiliation question,aggregate-level analyses cannot test the effects of questionwording directly. Between March and October 1992, we conducteda series of question-wording experiments, employing six statewidecomputer-assisted telephone interview (CATI) surveys of Michiganadults, including a four-wave panel study. Our analyses stronglysuggest that the Gallup measure responds more to short-termpolitical conditions and clearly demonstrate that the Gallupmeasure is less stable over time. These individual-level resultshelp explain why Gallup macropartisanship varies more over timethan aggregate measures of partisanship employing the standardSRC measure and raise questions about the degree to which onecan generalize from analyses using the Gallup data to the researchliterature on party identification.     

A theory of policy differentiation in single issue electoral politics

Voter preferences are characterized by a parameter s (say, income) distributed on a set S according to a probability measure F. There is a single issue (say, a tax rate) whose level, b, is to be politically decided. There are two parties, each of which is a perfect agent of some constituency of voters, voters with a given value of s. An equilibrium of the electoral game is a pair of policies, b ₁ and b ₂, proposed by the two parties, such that b _i maximizes the expected utility of the voters whom party i represents, given the policy proposed by the opposition. Under reasonable assumptions, the unique electoral equilibrium consists in both parties proposing the favorite policy of the median voter. What theory can explain why, historically, we observe electoral equilibria where the ‘right’ and ‘left’ parties propose different policies? Uncertainty concerning the distribution of voters is introduced. Let {F(t)} _{t ε T} be a class of probability measures on S; all voters and parties share a common prior that the distribution of t is described by a probability measure H on T. If H has finite support, there is in general no electoral equilibrium. However, if H is continuous, then electoral equilibrium generally exists, and in equilibrium the parties propose different policies. Convergence of equilibrium to median voter politics is proved as uncertainty about the distribution of voter traits becomes small.     

African American Women's Self-Concept: Implications for Career Decisions and Career Counseling

The multiple self-referent model (Brown-Collins & Sussewell, 1986) provides a comprehensive framework for understanding the personal, social, and historical aspects of self-concept formation in African American women and has important implications for understanding the complexity of career development issues for Black women. Excerpts from recorded interviews and autobiographical writings of four well-known African American women provide examples of the basic components of this model. Suggested interventions for career counseling with Black female clients are discussed.     

Is the GNP fractionally integrated?

The suitability of autoregressive fractionally integrated moving average (ARFIMA) processes for the modeling of US aggregate output is examined. We consider the two most widely used methods for the estimation of the fractionally differencing parameter and discuss the empirical results obtained by applying these methods to the quarterly post-war real GNP as well as to the quarterly post-war real GNP per capita. Contrary to previous findings, we conclude that evidence for a fractional degree of integration is poor.     

Government Risk Management Priorities: A Comparison of the Preferences of Asian Indian Americans and Other Americans

A survey was conducted of approximately 200 Asian Indian Americans and 200 other residents of New Jersey in order to understand the risk management priorities that they want government to have. We found that Asian Indian Americans, especially younger women, focused on personal/family risks, such as alcohol and drug abuse, sexual abuse, and domestic violence. The New Jersey comparison group, in contrast, placed war/terrorism and loss of health care services and insurance at the top of their priorities for government. These results suggest stressful acculturation-related issues within the Asian Indian community. Both populations want more risk management from government than they believe government is currently providing. Respondents who wanted more from government tended to dread the risk, be fearful of the consequences, trust government, and have a feeling of personal efficacy. Within the Asian Indian American sample, wide variations were observed by language spoken at home and religious affiliation. Notably, Muslims and Hindi language speakers tended not to trust government and hence wanted less government involvement. This study supports our call for studies of recent migrant populations and Johnson's for testing ethnic identity and acculturation as factors in risk judgments.     

Grounded Neural Networking: Modeling Complex Quantitative Data

The latest advances in artificial intelligence software (neural networking) have finally made it possible for qualitative researchers to apply the grounded theory method to the study of complex quantitative databases in a manner consistent with the postpositivistic, neopragmatic assumptions of most symbolic interactionists. The strength of neural networking for the study of quantitative data is twofold: it blurs the boundaries between qualitative and quantitative analysis, and it allows grounded theorists to embrace the complexity of quantitative data. The specific technique most useful to grounded theory is the Self‐Organizing Map (SOM). To demonstrate the utility of the SOM we (1) provide a brief review of grounded theory, focusing on how it was originally intended as a comparative method applicable to both quantitative and qualitative data; (2) examine how the SOM is compatible with the traditional techniques of grounded theory; and (3) demonstrate how the SOM assists grounded theory by applying it to an example based on our research.     

Surname analysis for estimating local concentration of Hispanics and Asians

Surname analysis is a potentially useful technique for identifying members of particular racial, ethnic, or language communities within a population. We review the existing state of the art for identifying persons of Hispanic or Asian origin, based on surnames distinctive of each group. We describe the logic of surname analysis, profile several available surname dictionaries, and illustrate their applications in local redistricting. Results of our ongoing validation studies suggest promising future directions for improving accuracy and broadening applications.This article is based on a paper presented at the annual Population Association of America meetings at Cincinnati, 1 April 1993.     

The sample autocorrelation function of I(1) processes

In case of a random walk the theoretical autocorrelations tend to one asymptotically. The sample autocorrelations, however, may decline rather fast even with large samples. We will explain this observation by deriving the asymptotic distribution that turns out to be closely related to the Dickey-Fuller (1979) distribution. Moreover we discuss the behaviour of the sample autocorrelations of integrated MA(1) and AR(1) processes. In order to prove our results we consider more general I(1) processes and apply the functional central limit theorem injected to time series analysis by Phillips (1987). We obtain unit root tests that are based on autocorrelation estimators of higher lags. We discuss their finite sample behaviour experimentally.