Implicit attitudes toward children may be unrelated to child abuse risk

Objective

To explore whether adults possess implicit attitudes toward children and whether those attitudes are especially negative among respondents who are high in child physical abuse (CPA) risk.

Methods

The present study used an implicit evaluative priming procedure. In this procedure, participants were instructed to make decisions about the evaluative implications of target words. These words were preceded by photographs of child faces or adult faces displaying positive, neutral, or negative expressions. Reaction times for the evaluative decisions were used as an index of the extent to which photos invoked negative or positive evaluative reactions.

Results

Results from 2 studies, the first conducted on a student sample (N = 90) and the second on a parent sample (N = 95), demonstrated that evaluative congruence between the facial expressions displayed in photographs and the target words facilitated responses. Furthermore, the results suggested that regardless of CPA risk, child faces, relative to adult faces, facilitated responses to negative target words, suggesting an out-group bias. This implicit out-group bias was not moderated by respondents’ CPA risk status.

Conclusions

Faces of children, relative to faces of adults, appear to activate negative information structures that facilitate evaluative decisions of negative stimuli, suggesting an out-group bias. Given that out-group biases typically lead to less favorable treatment of out-group members, additional research is needed to examine the pervasiveness of negative evaluative biases towards children and the potential implications of such biases on children's lives. Further, research examining whether high CPA risk parents and low CPA risk parents differ in how they manage initial negative evaluative reactions is needed.     

Keeping up with the Joneses: Institutional changes following the adoption of a merit aid policy

The increasing use by private colleges and universities of financial aid based on “merit”, as opposed to based solely on financial need has caused many to raise concerns that this type of aid will go mainly to higher income students crowding out aid to lower income students. However, some analysts suggest that by attracting more “almost full-paying” students through the use of merit aid, institutions will have more financial resources that they can use to increase their financial aid to low-income students and thus their enrollment. Results using data from the College Board's Annual Survey of Colleges and other secondary data sources suggest that the increased use of merit aid is associated with a decrease in enrollment of low-income and minority students, particularly at more selective institutions. Middle and bottom tier colleges may be offsetting costs with tuition increases, as the introduction of merit aid is accompanied by an increase in net costs.     

Peer assessment accounting for student agreement

Peer assessment has been gaining significant ground as a means of fostering an environment of accountability and responsibility for group projects in higher education. A popular peer assessment method assigns individual grades via a linear relationship to peer assessment scores. Using this method, a group member who receives his or her group’s average peer assessment score is assigned the instructor‐given group grade; the group member who receives a total peer assessment score of zero is assigned an individual grade of zero. Unfortunately, applying this method often requires time‐consuming exploratory data analysis because of the potential for the method to yield a high spread of grades, including grades over 100%. The present study proposes a modification, which accounts for the degree of student agreement. When the modified procedure results in a change from the group grade, the direction of change is always the same, but with smaller magnitude, requiring less subsequent data analysis and instructor time demands. Easy‐to‐modify SAS code for applying the method is presented in the Appendix.     

Does food insecurity at home affect non-cognitive performance at school? A longitudinal analysis of elementary student classroom behavior

This paper estimates models of the transitional effects of food insecurity experiences on children's non-cognitive performance in school classrooms using a panel of 4710 elementary students enrolled in 1st, 3rd, and 5th grade (1999-2003). In addition to an extensive set of child and household-level characteristics, we use information on U.S. counties to control for potential confounding effects of the local economic and noneconomic environment on children's household transitions between states of food insecurity and food security. The time horizon of our analysis affords insight into factors underlying children's formation of non-cognitive skills and the efficiency of classroom-based educational production in elementary school. Overall, we find significant negative developmental effects for children with food insecurity at home; and that children experiencing an early transition from food insecurity in 1st grade to food security in 3rd grade have even larger impairments that persist through 5th grade.     

Developing teaching self-efficacy in research institutions: A study of award-winning professors

The purpose of this study was to assess the sources of award-wining research professors’ (six women; six men) teaching self-efficacy through the framework of Bandura’s (1986) social cognitive theory. Semi-structured interviews revealed that mastery experiences and social persuasions were particularly influential sources of self-efficacy and that these sources tended to be closely related. Professors reported that their self-efficacy had generally stabilized within their first few years of assuming a tenure-track position. Participants framed negative events in adaptive ways that had little cost to their teaching self-efficacy.     

Using digital images of the zebra finch song system as a tool to teach organizational effects of steroid hormones: a free downloadable module

Zebra finch song behavior is sexually dimorphic: males sing and females do not. The neural system underlying this behavior is sexually dimorphic, and this sex difference is easy to quantify. During development, the zebra finch song system can be altered by steroid hormones, specifically estradiol, which actually masculinizes it. Because of the ease of quantification and experimental manipulation, the zebra finch song system has great potential for use in undergraduate labs. Unfortunately, the underlying costs prohibit use of this system in undergraduate labs. Further, the time required to perform a developmental study renders such undertakings unrealistic within a single academic term. We have overcome these barriers by creating digital tools, including an image library of song nuclei from zebra finch brains. Students using this library replicate and extend a published experiment examining the dose of estradiol required to masculinize the female zebra finch brain. We have used this library for several terms, and students not only obtain significant experimental results but also make gains in understanding content, experimental controls, and inferential statistics (analysis of variance and post hoc tests). We have provided free access to these digital tools at the following website: http://mdcune.psych.ucla.edu/modules/birdsong.     

Prescribed-time containment control with prescribed performance for uncertain nonlinear multi-agent systems

The existing studies on prescribed-time control cannot directly deal with nonlinear functions which don’t satisfy Lipschitz growth conditions. No results are available for prescribed-time containment control of pure-feedback UNMASs with prescribed performance. Therefore, completely unknown nonlinear function, prescribed-time tracking of system states and prescribed performance of containment errors are simultaneously considered in this paper. Fuzzy logic systems are utilized to approximate completely unknown nonlinear function. Prescribed-performance function is introduced and further incorporated into a novel speed function. Combining the proposed speed function and barrier Lyapunov function, this article presents a novel adaptive fuzzy prescribed-time containment control method which can guarantee, under prescribed performance, all followers converge to a convex formed by dynamic leaders in a prescribed time. Moreover, all tracking errors converge to predefined regions in a prescribed time. The effectiveness of the proposed prescribed-time containment control method are confirmed by strict proof and simulation.     

Novel model reference adaptive control laws for improved transient dynamics and guaranteed saturation constraints

In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.