Future Directions in Intimate Partner Violence Prevention Research

ABSTRACT

During the past 20 years, research on dynamics of intimate partner violence, risk factors, and treatment of intimate partner violence has flourished. However, research on the prevention of intimate partner violence is in its infancy. The current volume was developed in order to examine the state of the art in preventing intimate partner violence. To that end, this article offers a synthesis of recommendations for future research made by the authors in this volume and participants in the symposium on the prevention of intimate partner violence sponsored by the Department of Defense. A goal in compiling these recommendations is to foster more and better research into preventing intimate partner violence.     

A Note on Motor Learning Without Post-Response Knowledge of Results

The authors studied the adjustment of the 2 distinct known expressions of gait velocity, the velocity of the center of gravity (CG) and the velocity of the center of foot pressure (CP) at the end of the 1st step in 2 experimental situations: natural gait initiation (the control situation, CS) and heel-off gait initiation (the test situation, TS). Gait was initiated by 7 healthy participants, from an erect spontaneous posture in the CS and from a posture with heels raised in the TS, on a force platform at 3 self-selected speed conditions. Biomechanical data from the force platform were collected in both experimental situations, and the authors used a particular gait analysis based on the differential method of Y. Brenière (2003) in order to approach velocity modulation by means of step length and frequency. Results showed that CG and CP velocities were adjusted differently during heel-off gait initiation than during natural gait initiation. CP velocity, as compared with CG velocity, was overestimated in TS. Results also established the relevance of the expression of step velocity by means of step length and frequency: The central nervous system, taking into account the specific postural constraints of each experimental situation, uses a reference value and a regulating parameter to modulate step velocity. Moreover, the contributions of 1st step length and frequency to the expression of step velocity in TS and CS were different. Thus, a specific locomotor behavior corresponds to a given experimental situation that is characterized by its own initial biomechanical constraints.     

Uniform Test Assembly

In educational practice, a test assembly problem is formulated as a system of inequalities induced by test specifications. Each solution to the system is a test, represented by a 0–1 vector, where each element corresponds to an item included (1) or not included (0) into the test. Therefore, the size of a 0–1 vector equals the number of items n in a given item pool. All solutions form a feasible set—a subset of 2 ⁿ vertices of the unit cube in an n-dimensional vector space. Test assembly is uniform if each test from the feasible set has an equal probability of being assembled. This paper demonstrates several important applications of uniform test assembly for educational practice. Based on Slepian’s inequality, a binary program was analytically studied as a candidate for uniform test assembly. The results of this study establish a connection between combinatorial optimization and probability inequalities. They identify combinatorial properties of the feasible set that control the uniformity of the binary programming test assembly. Computer experiments illustrating the concepts of this paper are presented.     

Classification of dog barks: a machine learning approach

In this study we analyzed the possible context-specific and individual-specific features of dog barks using a new machine-learning algorithm. A pool containing more than 6,000 barks, which were recorded in six different communicative situations was used as the sound sample. The algorithm's task was to learn which acoustic features of the barks, which were recorded in different contexts and from different individuals, could be distinguished from another. The program conducted this task by analyzing barks emitted in previously identified contexts by identified dogs. After the best feature set had been obtained (with which the highest identification rate was achieved), the efficiency of the algorithm was tested in a classification task in which unknown barks were analyzed. The recognition rates we found were highly above chance level: the algorithm could categorize the barks according to their recorded situation with an efficiency of 43% and with an efficiency of 52% of the barking individuals. These findings suggest that dog barks have context-specific and individual-specific acoustic features. In our opinion, this machine learning method may provide an efficient tool for analyzing acoustic data in various behavioral studies.     

Portrayal of body weight on children's television sitcoms: a content analysis

Television programs portray characters with idealized body types that for most viewers are unattainable. These body types have become a common source of comparison for many young viewers who evaluate their own self-worth and bodies based on the models they see on television. This study examines body weight, both in terms of frequency and portrayals, focusing on how preadolescent and adolescent characters’ bodies are presented on the sitcoms from three children's television networks. The results indicate that while children's situation comedies have relatively few overweight characters, this small percentage closely parallels national figures. Male and female characters do not differ in their distribution across weight categories. However, when character ethnicity is factored, significant shifts occur. Surprisingly, no differences were observed in the portrayal of physical and mental attributes among weight categories except in social popularity where overweight characters were not as embedded in social networks. Compared to other relevant studies, this research provides some evidence that the treatment and portrayal of overweight characters in children-targeted sitcoms is more positive, equitable, and less stereotypical than in other programming venues and that children are experiencing body type diversity in these fictional portrayals. Nonetheless, above average weight characters still suffer some social marginality and ethnic misrepresentation.     

无意视盲的认知神经机制

无意视盲现象是指即使某些刺激物出现在视野中, 观察者也并没有觉察到这些刺激物的存在。这种现象在我们的现实生活中普遍存在, 它是许多交通和医疗事故的罪魁祸首。回顾前人的研究结果我们发现, 从认知行为角度出发, 无意视盲主要由两方面原因引起, 即“资源有限”与“注意定势”。一般情况下, “资源有限”与“注意定势”会共同导致无意视盲; 但有时候, “注意定势”也会独立于“资源有限”直接导致无意视盲。另外, 从大脑神经机制的角度来看, “资源有限”与“注意定势”作用于大脑加工的中后期, 即使产生无意视盲, 意识加工脑区对非预期刺激也进行了一定的认知加工, 但是否能进入到意识层面, 一方面取决于刺激呈现后中期枕顶部位的意识输入, 另一方面取决于与刺激驱动相关的颞顶联合区的激活程度以及与记忆负荷相关的顶内沟的抑制程度。     

Output‐sensitive complexity of multiobjective combinatorial optimization

We study output‐sensitive algorithms and complexity for multiobjective combinatorial optimization problems. In this computational complexity framework, an algorithm for a general enumeration problem is regarded efficient if it is output‐sensitive, that is, its running time is bounded by a polynomial in the input and the output size. We provide both practical examples of multiobjective combinatorial optimization problems for which such an efficient algorithm exists as well as problems for which no efficient algorithm exists under mild complexity theoretic assumptions.     

粗糙集在项目认知属性标定中的应用

认知诊断是新一代测量理论的核心, 对形成性教学评估具有重要意义。项目认知属性标定是认知诊断中一项基础而重要的工作,现有的项目认知属性辅助标定方法的研究工作很少, 并且在应用上存在诸多局限。课堂评估是认知诊断应用的理想场所,但课堂评估中项目的选取具有随意性, 教师难以在短时间内准确标识项目认知属性。本研究首次提出采用粗糙集方法对项目认知属性进行标定, 该方法无需太多被试和项目, 亦无需已知项目参数, 且能当场诊断出结果, 适于采用纸笔测验的课堂评估。通过Monte Carlo模拟研究表明：采用粗糙集方法能迅速地对项目认知属性进行标定, 并具有较高的标定准确率; 而且, 项目认知属性越少、或被试估计判准率越高、或失误率越小则项目认知属性标定的准确率越高。粗糙集方法的引入, 对拓展认知诊断的应用范围, 真正实现其辅助性教学功能, 具有重要作用。     

On Evans's Vague Object from Set Theoretic Viewpoint

Gareth Evans proved that if two objects are indeterminately equal then they are different in reality. He insisted that this contradicts the assumption that there can be vague objects. However we show the consistency between Evans's proof and the existence of vague objects within classical logic. We formalize Evans's proof in a set theory without the axiom of extensionality, and we define a set to be vague if it violates extensionality with respect to some other set. There exist models of set theory where the axiom of extensionality does not hold, so this shows that there can be vague objects.