Variables Affecting Readiness to Benefit From Career Interventions

This article identifies and briefly describes the broad range of variables that may influence clients’ readiness to benefit from career interventions. The article also discusses consequences of low readiness for effective use of career interventions and addresses implications for practice as well as for future research. Variables contributing to low readiness for effective use of career interventions include personal characteristics and circumstances; knowledge of self, options, and decision making; and prior experience with career interventions. Consequences of low readiness for using career interventions include premature disengagement, negative perception of skills and interests, selective acquisition of incomplete information, premature choice foreclosure, protracted exploration, dependent decision‐making style, and poor evaluation of options.     

Computer‐Assisted Career Guidance Systems: A Part of NCDA History

The first computer‐assisted career planning systems were developed in the late 1960s and were based soundly on the best of career development and decision‐making theory. Over the years, this tradition has continued as the technology that delivers these systems’ content has improved dramatically and as they have been universally accepted as effective tools for career guidance practice. Although their widespread use in the United States is currently affected by financial conditions, the potential for using these systems in developing countries as a part of their implementation of career guidance services is promising.     

Good Effects of Bad Feelings: Negative Affectivity and Group Decision‐making

Extending the growing interest in the relationship between affect and workgroup processes, we propose that groups make better use of their distributed information and therefore make better decisions when group members are higher in negative affectivity. In an experiment, we studied the influence of negative affectivity when information was distributed among group members and when group members had fully shared information. Results indicated that negative affectivity indeed stimulates group information processing and decision quality when information is distributed among group members.     

Takacs–Fiksel Method for Stationary Marked Gibbs Point Processes

Abstract. This article studies a method to estimate the parameters governing the distribution of a stationary marked Gibbs point process. This procedure, known as the Takacs–Fiksel method, is based on the estimation of the left and right hand sides of the Georgii–Nguyen–Zessin formula and leads to a family of estimators due to the possible choices of test functions. We propose several examples illustrating the interest and flexibility of this procedure. We also provide sufficient conditions based on the model and the test functions to derive asymptotic properties (consistency and asymptotic normality) of the resulting estimator. The different assumptions are discussed for exponential family models and for a large class of test functions. A short simulation study is proposed to assess the correctness of the methodology and the asymptotic results.     

Premarital sexual permissiveness of American and Chinese college students: A cross‐cultural comparison

Employing the Reiss scale of premarital permissiveness, the author compared attitudes toward kissing, petting and coitus among American and Chinese college students. The data were composed of self‐administered questionnaires completed in class by 227 students in a state university in Texas, and by 708 students in a national university in Taiwan. As expected, Chinese students were far less permissive than American students. The pattern of less permissiveness for females than for males was preserved across the two cultures. Chinese students tended to follow the traditional code of sexual mores, while their American counterparts tended to follow the code of “permissiveness with affection.” Explanations are proffered and speculations are attempted for the Sino‐American disparities in permissiveness by selected social variables.     

Staff responses to age‐related health changes in people with an intellectual disability in group homes

The purpose of this study was to explore how supervisors in group homes caring for people with intellectual disability responded to the development of age‐related health changes in their residents. Ten group home supervisors working in the disability sector were interviewed once. Data were analysed using Dimensional Analysis. The study identified several factors related to whether a resident could stay ‘at home’ or would need to be moved to residential aged care (nursing home) including: nature and extent of group home resources, group home staff comfort with residents’ health changes, staff skill at navigating the intersection between the disability and ageing sectors, and the supervisor’s philosophy of care. The ability of older people with an intellectual disability to ‘age in place’ is affected by staff knowledge about and comfort with age‐related illnesses, staff skills at navigating formal services, staffing flexibility, and the philosophy of group home supervisors. Despite the growing international concern for the rights of people with disability, particularly in relation to decision making, questions about the older person’s choice of residence and participation in decision making about what was best for them, were almost nonexistent. Rather, decisions were made based on what was considered to be in ‘the best interest’.     

Rural‐Urban Differences in Environmental Concern in Canada

Abstract Distinctions between rural and urban populations are well documented in environmental sociology literature. Rural and urban places may exert different influences on participation in environmentally supportive behavior (ESB) as well as on other forms of environmental concern (EC). The influence of these distinct geographies may be due to present circumstances or because of childhood socialization in these places. Using data from a national survey in Canada (n=51 664), we use cognitive (basic values, environmental worldview, and environmental attitude) and behavioral indicators (public and private sphere) of EC to explore differences among rural and urban populations and we include analyses accounting for place of socialization. We extend the conventional private sphere category of ESB by including stewardship behaviors. Results showed few differences between rural and urban residents on indicators of EC. Rural residents, however, scored higher on altruistic values, placed a higher priority on the environment, and reported higher participation in recycling and stewardship behaviors. Analysis that included place of socialization showed differences on environmental worldview, basic values, and some ESB. In terms of ESB, we conclude that residence and place of socialization may be less of a factor than opportunity and highlight the importance of providing services and facilities. We recommend future research on residence and ESB include a variety of behaviors that reflect opportunities for both rural and urban residents.     

Inferring an Augmented Bayesian Network to Confront a Complex Quantitative Microbial Risk Assessment Model with Durability Studies: Application to Bacillus Cereus on a Courgette Purée Production Chain

The Monte Carlo (MC) simulation approach is traditionally used in food safety risk assessment to study quantitative microbial risk assessment (QMRA) models. When experimental data are available, performing Bayesian inference is a good alternative approach that allows backward calculation in a stochastic QMRA model to update the experts’ knowledge about the microbial dynamics of a given food‐borne pathogen. In this article, we propose a complex example where Bayesian inference is applied to a high‐dimensional second‐order QMRA model. The case study is a farm‐to‐fork QMRA model considering genetic diversity of Bacillus cereus in a cooked, pasteurized, and chilled courgette purée. Experimental data are Bacillus cereus concentrations measured in packages of courgette purées stored at different time‐temperature profiles after pasteurization. To perform a Bayesian inference, we first built an augmented Bayesian network by linking a second‐order QMRA model to the available contamination data. We then ran a Markov chain Monte Carlo (MCMC) algorithm to update all the unknown concentrations and unknown quantities of the augmented model. About 25% of the prior beliefs are strongly updated, leading to a reduction in uncertainty. Some updates interestingly question the QMRA model.