Emotional intelligence, reflective abilities and wellbeing in social workers

Research reportIn order to inform the curriculum and the development of supportive structures to support the work-related wellbeing of trainee social workers, this research project had several aims. It examined the key motivators to enter social work, together with the sources of social support and the coping strategies that students draw on to help them manage the demands of study and placement experiences Several emotional and social competencies (i.e. emotional intelligence, reflective ability, empathy and social competence) are also investigated as potential predictors of resilience. Also examined was whether resilience predicted psychological distress, and the role played by resilience in the relationship between emotional intelligence and distress was assessed

Cultivating Empathy: New Perspectives on Educating Business Leaders

Beyond rules, procedures, and manuals lie relationships. Jettisoning a formal hierarchical company structure allows all levels of management and employees to positively interact – this is where the key driver of “empathy” is so critical to continue building these relationships and molding a common organizational purpose

Climate Change and Farm Use of Weather Information

More rapid than normal global climate change as represented by rising temperatures and more erratic and severe weather events have heightened the interest in how farmers use weather information. The greenhouse influence through driving climate change will likely be affecting agricultural efforts for some years to come. It behooves us to pay attention to this phenomenon, and especially put effort into understanding how farmers will respond to information about climate generally and forecasts in particular. This research is being funded by the U.S. Department of Commerce, National Oceanic and Atmospheric Administration. To address this issue farmers were surveyed in three major agroecological zones representing 1) a western Corn Belt, rainfed corn-soybean regime, 2) a central Great Plains irrigated corn-soybean regime, and 3) a central Great Plains irrigated continuous corn regime. Each of these zones is represented in three counties in eastern Nebraska. To better reflect farmers' weather related needs and issues, focus groups were held in each county to engage farmers in helping the researchers to design the survey instrument. The fact we used focus groups added an intriguing flavor to the study. Between 15-20 farmers in each zone were involved. These farmers were paid $25 for a 2-hour session that culminated in a provided lunch. Each session was also videotaped, providing the opportunity for all members of the research team to see the results of the event (in that only 3-4 members of the larger multidisciplinary research team were allowed to attend an event, due to concerns over affecting farmer responses). The focus was on the farmers' reactions to a series of questions prepared beforehand by the research team, all of which stirred lively dialogue on how farmers actually use weather information. The result was a substantially improved questionnaire. We also sent drafts back to farmer participants for final reviews, and subsequent adjustments were then made reflecting the way they used the words and understood the survey questions. The qualitative data from the focus group events ultimately influenced not only the way questions were asked but also how the modeling is done, and, especially, how the model results are interpreted. A total of 2211 questionnaires were sent, in two separate mailings. There was also a follow-up reminder card. Farmers were offered a payment of$25 to return the questionnaire. A total of 28% took the offer and the overall return rate was 33%, with 698 usable questionnaires in the econometric analysis. A distinctive aspect of this study is the fact that the research team involves active participation not only by agricultural economists but also by a psychologist and a social psychologist, as well as two meteorologists, and an agronomist (who is also a GIS specialist). The result is a nontraditional behavioral economics approach that is sensitive to the climate and agronomic realities faced by farmers in these zones. This approach has a unique two-fold feature; first, it puts special attention on underlying motives, and second, asks whether there may be a complex expression of both private (self) and public (other, community) interest in how forecasts influence farm level decisions. Yet, the modeling still reflects standard derived demand theory and the general expectancy-value or subjective utility perspective, i.e. that farmers have beliefs about fact events and values relating to the outcomes from those events, and that the demand for weather information is derived from the value (profit, sense of well-being, risk-reducing value) it produces for them. The beliefs represent probability statements about outcomes and the values represent the utility or profit related transformations of meaning about the farmer perceptions of the outcomes. The econometric analysis uses proxy measures of the expectancy-value as independent measures, along with such variables as financial capability of the farmer as represented in farm sales, to explain in a Tobit kind of framework 1) the probability of applying weather forecast information since it influences farm level decision(s), and 2) the extent to which this forecast information is influencing these decision(s). The set of four Tobit models in Table 1 test the influence of recent past and current experience (RPE), short (STF) and long-term forecasts (LTF) on 1) agronomic (e.g. selecting the crop type, spraying), 2) insurance, and 3) marketing decisions, within recent past experience/short-term and long-term forecasts. To test the models, we created four indices represented in balance (joint and nonseparable ratio of public (other) to private (self) interests); attitude as a construct of personal belief and value system, influence of social norms, household and community members, county extension, etc; farmers' need for internal control over crop production; and farm sales representing financial limitations. Preliminary analyses suggest that all the farm decisions are influenced by weather forecast information at a different intensity (Table 1). The probability of that influence increases with balance, as the farmer puts more effort into pursuing the self over the community interests. Influence of others and social norms intensify the use of weather information in the decisions as well. Those who want more control over the farm are likely to be more influenced by weather forecasts. Finally, influence of weather forecasts becomes greater as gross farm income (sales) increases. Other intriguing interpretations are suggested by the changes in the size of the parameter elasticities and marginal effects3, e.g. the control parameter is substantively smaller in the insurance decision, which suggests farmers see insurance as offsetting the need for more control over their decisions. As another example, the balance in private and public interests is less significant and less a factor in the very personal, private marketing decision in contrast to "how one farms" (which is likely more sensitive to community scrutiny) in the agronomic decisions. The larger paper explores these refinements in greater detail. Table 1. Intensity of Weather Forecast Influence on Farm Decisions. Variables Agronomy (Cur. Rec. Past Exp. & Short term forecasts) decisions Agronomy (Long Term Forecasts) decisions E1 E 2 ME 1 ME 2 E 1 E 2 ME 1 ME 2 Balance -.37b -.37b -1.109b -.012b -.23a -.24a -.637a -.0202a Attitude .62c .62c .495c .0052c .71c .72c .560c .0178c Norms .12c .12c .153c .0016c .09b .09b .102b .0032b PBC .15c .15c .157c .0017c .19c .19c .178c .0056c Farm Sale .07b .07b .086b .0009b .02 .02 .024 .0008 Easting .06b .06b -2.2E-6b -2.3E-8b -.01 -.01 3.7E-7 1.2E-8 Insurance decisions Marketing decisions Balance -.12 -.13 -.247 -.033 -.29a -.29a -.779a -.040a Attitude .93c .98c .674c .089c .58c .59c .486c .025c PBC .07 .07 .048 .006 .13b .13b .119b .006b Farm Sale .18c .19c .164c .022c .20c .20c .238c .012c Notes: Dependent variable is the degree of influence of climate and weather information and forecasts. a p<0.10, b p<0.05, c p<0.001. 3 E1 is the elasticity at the mean that represents the percentage change in the probability that the weather and climate forecast and information influences decisions at all, and; E2 is the elasticity at the mean for those who are being influenced, the percentage change in the degree of influence. ME1 is the effect of the expected value for the weather and climate already influenced farmers; ME2 is the effect of the probability of being influenced by climate and weather information (elasticity of influence).Farm Management,

Social Influence and Individual Difference in Experimental Juries

In a jury decision-making, individuals must compromise in order to reach a group consensus. If individuals compromise for non-rational reasons, such as a preference for conformity or due to erroneous information, then the final decision of the group may be biased. This paper presents original experimental data which shows that groups do have a significant tendency to compromise in jury-like settings. Econometric evidence also shows that features of groups, including the generosity of the group overall, will dictate the extent of compromise. The data also reveal that individual traits such as gender and capacity for empathy are associated with the extent of compromise in a jury-type setting. The implications are that interactions between individual and group characteristics limit the objectivity of decision-making

Cultivating Systems Leadership in Cross-Sector Partnerships: Lessons from the Linked Learning Regional Hubs of Excellence

Investments in the social sector have become increasingly complex, with many foundations shifting from supports for single organizations toward more systemic strategies focused on improving outcomes for entire communities. As a result, the field has become awash in regional, or place-based, investments that rely on cross-sector partnerships and networks to drive change. These efforts require coordination among stakeholders across all levels of the practice and policy continuum – from direct service providers, to nonprofit intermediaries, funders, advocacy organizations, and policymakers.It is in this context, and in the spirit of continuous learning, that The James Irvine Foundation's Linked Learning Regional Hubs of Excellence investment serves as a systems change experiment, offering insights and critical lessons that can inform others undertaking similar work. The aim of this Issue Brief – authored by Equal Measure and Harder+Company – is to contribute to field dialogue and learning about the role of leadership in complex systems change strategies, particularly those focused on producing equitable impacts in college and career readiness.Equal Measure and Harder+Company serve as the evaluators of The James Irvine Foundation's Linked Learning Regional Hubs of Excellence. They work in partnership with Jobs for the Future, the intermediary and technical assistance provider for this initiative