Uncontrollable Causes Research Articles

Research on CC-SSBLS Model-Based Air Quality Index Prediction

Establishing reliable and effective prediction models is a major research priority for air quality parameter monitoring and prediction and is utilized extensively in numerous fields. The sample dataset of air quality metrics often established has missing data and outliers because of certain uncontrollable causes. A broad learning system based on a semi-supervised mechanism is built to address some of the dataset’s data-missing issues, hence reducing the air quality model prediction error. Several air parameter sample datasets in the experiment were discovered to have outlier issues, and the anomalous data directly impact the prediction model’s stability and accuracy. Furthermore, the correlation entropy criteria perform better when handling the sample data’s outliers. Therefore, the prediction model in this paper consists of a semi-supervised broad learning system based on the correlation entropy criterion (CC-SSBLS). This technique effectively solves the issue of unstable and inaccurate prediction results due to anomalies in the data by substituting the correlation entropy criterion for the mean square error criterion in the BLS algorithm. Experiments on the CC-SSBLS algorithm and comparative studies with models like Random Forest (RF), Support Vector Regression (V-SVR), BLS, SSBLS, and Categorical and Regression Tree-based Broad Learning System (CART-BLS) were conducted using sample datasets of air parameters in various regions. In this paper, the root mean square error (RMSE) and mean absolute percentage error (MAPE) are used to judge the advantages and disadvantages of the proposed model. Through the experimental analysis, RMSE and MAPE reached 8.68 μg·m−3 and 0.24% in the Nanjing dataset. It is possible to conclude that the CC-SSBLS algorithm has superior stability and prediction accuracy based on the experimental results.

A measure of attributions for peer victimization: psychometric properties and differences among bullying roles

ABSTRACT Attributional processes about why outcomes occur constitute an important mediating mechanism that can explain different reactions of both the targets of harassment and their peers. The present study aimed to evaluate the psychometric properties of a measure of attributions for victimization among adolescents, using Confirmatory Factor Analyses, and to examine differences among roles (i.e., not involved, bullies, victims, bully-victims) in self-blame attributions, by means of testing invariance. The sample consisted of 1,207 adolescents (54% females; Mage = 14.89; SD = 1.39). The results showed a multidimensional structure of the scale with three factors (Characterological self-blame, Behavioral self-blame, and External Attribution). Partial invariance was found across different roles, highlighting a difference in the latent means of Characterological Self-Blame, higher in the victim group than in the other roles. The findings suggested how victims showed biases in their interpretations of social situations attributing the negative experience to internal, stable, and uncontrollable causes.

Exploring the effects of positive emotions and attribution on helping behaviors after exposure to meaningful and pleasurable movies

ABSTRACT This study examined whether elevation elicited by meaningful movie clips led to helping regardless of whether a stranger’s need for help is attributed to a controllable or an uncontrollable cause. It also compared elevation against positive-valenced affective state in facilitating prosocial behavior. A randomized, between-subject laboratory experiment was conducted with 208 undergraduate participants in the United States approximately one week after they completed a pretest survey. Although participants experienced the induced emotional state, neither of these two types of positive emotions explained their helping behavior. This points to the nuanced nature of the relationships between positive emotions and helping. The role of media content types, attribution, and prosocial personality are also discussed.

Why am I so successful? Self-presentation and deliberative attributions of success in entrepreneurship

This study explores the complexities of causes of success mentioned in entrepreneurs' narratives in a broadcasted context. Building on strategic self-presentation and attribution theories, we employed inductive methods to map the configurations of public narratives explaining entrepreneurial success. The data analyzed were gathered from 173 reflective interviews featuring entrepreneurs on the United States' National Public Radio, using machine learning techniques for semantic content analysis. The results show that entrepreneurs can adopt three strategic presentation narratives to explain success in entrepreneurship. Significantly different patterns emerge in the three strategic narrative configurations. First, “lucky charming” narratives reflect an ingratiation strategy, mentioning external and uncontrollable causes of success to increase the entrepreneurs’ likability for the audience. Second, “work striving” narratives use self-promotion strategies to push for recognition of accomplishments, efforts, and intellectual abilities. Third, “social connecting” narratives simultaneously make use of ingratiation and exemplification strategies, including capitalizing on the positive signals given by the social support attracted during their entrepreneurial journey. These three discourse patterns have implications for influencing reputation and driving business- and personal-related outcomes. The findings provide a better understanding of deliberate appearances by entrepreneurs in broadcast contexts and tools for nascent entrepreneurs to leverage their role models among those with acclaimed entrepreneurial success.

Brief Research Report: Teachers’ Gender-Differentiated Attributions

Teachers play a fundamental role in guaranteeing an inclusive teaching practice using Educational Robotics (ER). However, they may hold gender-differentiated views of their students’ academic abilities and aptitudes in ER. This quasi-experimental test investigated gender-differentiated attributions and behavioral intentions of N = 158 Italian learning support teachers (LST) answering a questionnaire at the end of a post-graduate ER course. Participants read one of two vignettes regarding a student failing an ER activity in class: − (1) a boy; or (2) a girl. Then participants answered items based on measures that assessed their gender stereotypes, attributions for the child’s failure, and hypothetical intentions to use ER with the same child. Results of moderation analyses indicated that the failure of the depicted girl was attributed to internal, stable and uncontrollable causes (i.e., low abilities in ER) to a greater extent than the same failure of the depicted boy, among LST with high levels of gender stereotypes. Furthermore, LST with high levels of gender stereotypes declared less intention to use ER with the depicted girl as compared with the depicted boy.

Validation of Herek's attitudes toward lesbian women and gay men scale among undergraduates in mainland China.

The lack of a standardized reliable and valid instrument makes it difficult to measure attitudes toward lesbian women and gay men (ATLG) consistently and thus poses a challenge to compare and contrast intervention measures. This study aimed to validate Herek’s ATLG scale among undergraduates in mainland China and identify factors associated with negative attitudes toward LG. A total of 6,036 eligible undergraduates conveniently drawn from 30 provinces across mainland China were randomly split in half. Item analysis was first used to select unrelated or redundant items for deletion. Exploratory factor analysis (EFA) were then conducted on the first half of the sample (n = 3,001), followed by confirmatory factor analysis (CFA) and reliability analysis in the second half (n = 3035). Logistic regression analyses were finally carried out to identify their determinants. Six items were removed from the item analysis. EFA supported the existence of two factors (ATL and ATG). CFA results indicated that the two-factor model fit the data better than the one-factor model. Logistic regression analyses indicated that being female, majoring in non-health-related disciplines, attributing homosexuality to uncontrollable causes, non-adherence to traditional gender norms and exposure to homosexual content were significantly associated with less negative attitudes toward both L and G. Urban students were marginally less likely to express negative attitudes toward L but not G, while non-heterosexuals and those who had prior personal contact with homosexuals exhibited less negative attitudes toward G but not L. However, grade showed no significant associations with either ATL or ATG. The retained 14-item version of Herek’s ATLG scale has been proven to be a reliable and valid tool. Furthermore, ATL and ATG were determined by different factors and thus would be treated separately. In order to reduce negative attitudes toward LG among undergraduates in mainland China, a comprehensive intervention plan such as conducting comprehensive sex education and pushing the process of legalizing same-sex marriage should be designed, implemented and evaluated.

Machine Learning Approach for Classifying Power Outage in Secondary Electric Distribution Network

Power outage is the problem that hinders social and economic development especially for developing countries like Tanzania. Frequent power outages damage electric equipment, and negatively affect the industrial production process. Power outages cannot be completely eradicated due to uncontrolled cause like natural calamities but technical challenges can be managed and hence reducing power outages. The existing manual methods used to locate power outage like customer calls is inefficient and time consuming. On the other hand, modern method like the Advanced Metering Infrastructure (AMI) still faces a challenge in effectively classifying power line outage due to the nature of imbalanced datasets. Therefore, there is a need to develop a Machine Learning (ML) model to accurately classify power line outage. In this study, machine learning models are constructed from ensemble algorithms and tested using outage AMI data from 2012 to 2019 with 2 hours interval records. We propose the following ensemble-based machine learning approach to enhance classification; data sampling, algorithm weighting and finally ensembling. Results show that the Hybrid Stacking Ensemble Classifier (HSEC) model outperforms the others by accuracy of 0.981 G-mean, followed by Extra tree with accuracy of 0.964 G-mean. This model can be used in power line outage classification in any Secondary Electrical Distribution Network (SEDN). This study can be extended to locate power outage to household.

Slow Learner Student Profile (Case Study at MAN 1 Padang Lawas)

This research is motivated by the phenomenon of students who are slow in learning, for example: slow in accepting or capturing learning, slow in managing lessons, slow reading, slow reading comprehension, slow working, slow doing assignments, slow in solving problems and so on. Children who are slow to learn are called slow learners. The inability of these students will affect themselves and affect others. The purpose of this study were (1) To describe the case of slow learner students, (2) to determine the form of slow learner student delay, (3) to determine the case study of slow learner students. This type of research is a qualitative descriptive study in the form of a case study. The subjects in this study were five students at MAN 1 Padang Lawas North Sumatra. The data collection instruments used in this study were interview, observation, and documentation guidelines. The data analysis technique used in this research is thematic analysis by conducting transcripts of interviews that have been verbatim. The results of this study reveal the profile of the slow learner students carried out, the five subjects were unable to achieve their learning objectives in the process or their learning activities, the five subjects had difficulty memorizing, counting, and several other obstacles. Unlike other students in their socialization, the five subjects preferred to be silent and did not play an active role in the class. Meanwhile, their emotional uncontrollable causes they cannot achieve their goals in learning well. Based on the research results, it is suggested that guidance and counseling teachers can be used as a guideline in determining the delivery of BK services, especially those related to slow learner students through information services, content mastery services and individual counseling services.

An attribution-based motivation treatment to assist first-generation college students reframe academic setbacks

First-generation college students face unique obstacles that can erode their psychological well-being, academic motivation, and educational development during school-to-college transitions. Although research shows attribution-based interventions foster academic attainment among at-risk students (Hamm et al., 2020; Perry & Hamm, 2017), little is known about treatment efficacy for students with socioeconomic risk factors such as first-generation status (Gutiérrez, 2008). In a randomized treatment study, we administered attributional retraining (AR) to first- and continuing-generation college students who differed in academic control beliefs (low, high) in an online two-semester introductory psychology course. For low-control first-generation students, AR recipients outperformed their no-AR peers by a letter-grade (B vs. C+) and were 55% less likely to drop the course. AR-grade efficacy was mediated by causal attributions and control beliefs in a path sequence specified by Weiner’s (1979, 1985, 2018) attribution theory. AR decreased attributions to uncontrollable causes, which negatively predicted final course grade and increased academic control beliefs, and these positively predicted final course grade. These findings advance motivation intervention research by demonstrating that an AR treatment can have salutary benefits for first-generation students mediated by theory-derived cognitive processes.

Adaptive Causal Thinking About Mobility Challenges: Implications for Quality of Life

Weiner’s attribution theory posits that it is adaptive to ascribe challenges to controllable causes (e.g., insufficient effort, bad strategies) and maladaptive to ascribe them to uncontrollable causes (e.g., old age). This is supported by our prior research that showed a heightened risk of mortality when mobility challenges were attributed to old age. The present pilot study randomly assigned older adults (N=36) in a day hospital to either an attributional retraining (AR) intervention group that viewed a video intended to shift causal thinking regarding mobility challenges (uncontrollable→controllable causes), or to a comparison group (No-AR). Participants completed a Time1 survey, the AR intervention (one week later), and a Time2 follow-up survey two weeks later. A manipulation-check revealed that AR was effective in shifting causal thinking away from maladaptive causes; a decline in the endorsement of the old age attribution was observed in the AR group (Ms=2.61 vs. 2.06; p=.02), but not in the No-AR group (Ms=2.45 vs. 2.35, p=.30). The AR and No-AR groups were equivalent at Time 1 on two quality-of-life outcomes: helplessness and perceived control (PC) over health. However, helplessness declined (Time1-Time2) in the AR group (Ms=1.13 vs. 0.73, p=.03), whereas it was relatively stable in the No-AR group (Ms=1.42 vs. 1.26, p>.20). Moreover, PC increased marginally in the AR group (Ms=6.50 vs. 6.69; p=.06), but declined in the No-AR group (Ms=6.20 vs 5.45, p=.05). Together, these findings suggest that attributions can be shifted away from uncontrollable causes and that this shift can have a protective effect that benefits quality-of-life.

A Causal Analysis of Conglomerate Bankruptcies

Purpose - Strategic causes for the failure include unrealistic growth, overexpansion, unfamiliar new markets, volume obsession, unrealistic promises and poor project selection. Organizational causes are insufficient capital and profits, lack of business knowledge, poor financial management, poor sales skills, inadequate marketing, poor leadership, poor leadership transfer, project losses, poor field performance and owner bankruptcy. Uncontrollable causes include industry and economic weakness and banking and surety changes. While helpful, the list provides insufficient clarity regarding the causal roots of failure. Research design, data and methodology - The research framework to organize the information involved with many of the recent and large failures in the industry. Results - This research then identified five dominant root causes - excessive egoism, poor strategic leadership, too much change, loss of discipline and inadequate capitalization. Conclusion - Finally, additional input from external forces may accelerate the firm's pace to failure. It is important on the development of diagnostic tools that are based on this model and that will provide new ways to assess a conglomerate's level of risk for incurring a financial crisis.

Exploring the Public Perception of Depression: Interplay between the Attribution of Cause and Narrative Persuasion

ABSTRACT Improving awareness and mitigating stigma related to depression have been a concern to both health communicators and practitioners. This study conducted a 2 (narrative vs. non-narrative) × 2 (high controllability vs. low controllability) experiment (N = 242) to test the interaction effects of narrative persuasion and cause controllability of depression. The results show that narrative messages attributing depression to an uncontrollable cause increase identification, feeling of pity, and intention to help. However, the study finds that the positive effects of narrative messages are conditional, and they may be less effective than non-narrative messages when the cause of depression is controllable. Also, the findings suggest identification as the underlying mechanism of such interaction effects on emotional and behavioral responses. Theoretical and practical implications are discussed further.

Compassion-Cultivating Pedagogy

AbstractPrevious studies suggest that narrative fiction promotes social justice by increasing empathy, but critics have argued that the partiality of empathy severely limits its effectiveness as an engine of social justice, and that what needs to be developed is universal compassion rather than empathy. We created Compassion-Cultivating Pedagogy (CCP) to target the development of two social-cognition capabilities that entail compassion: (1) recognition of self-other overlap and (2) cognizance of the situational, uncontrollable causes of bad character, bad behavior, and bad life-outcomes. Employing a pre/post within- and between-subjects design, we found that students in the CCP classes, but not students in conventionally taught classes, improved in these two areas of social cognition and also exhibited increased preference for compassionate social policies for stigmatized groups. This finding suggests that pedagogy can play a significant role in literature’s contribution to social justice, and that further efforts to develop and test pedagogies for improving social cognition are warranted.

Maternal Attribution and Chinese Immigrant Children’s Social Skills: The Mediating Role of Authoritative Parenting Practices

SYNOPSIS Objective . This study explores the contributions of Chinese immigrant mothers’ parenting cognitions and parenting practices to their children’s social skills. Design . We used a cross-sectional design to examine the mediating role of authoritative parenting in associations between Chinese immigrant mothers’ parenting attributions and their children’s social skills. Chinese immigrant mothers (N = 208, M age = 37.36 years) reported their attributions regarding successes and failures in their daily caregiving experiences, authoritative parenting practices, and demographic information. Their preschool children’s (M age = 4.51 years, 46.2% females) social skills in school were rated by their teachers. Results . Maternal attributions of successful events to uncontrollable causes and unsuccessful events to controllable causes were associated with more authoritative parenting. In turn, more authoritative parenting was associated with more competent social skills in children. In contrast, maternal attributions of successful events to controllable causes and unsuccessful events to uncontrollable causes were associated with less authoritative parenting, which in turn was associated with poorer social skills in children. Conclusions . Promoting Chinese immigrant mothers’ attributions that preserve positive efficacy during daily parenting tasks may enhance their engagement in warm, autonomy-promoting and regulatory parenting, which in turn may facilitate their children’s social skills.

The Role of Psychological Stigmatization in Unemployment Discrimination

Discrimination against the unemployed operates through attributions, is unjustifiable, and is nearly instantaneous. Experimental Studies 1 and 2 find that unemployment discrimination operates through attributions, as emphasizing an uncontrollable and external cause for unemployment onset alleviates discrimination. Experimental Studies 3 and 4 find that unemployment stigma is unjustifiable on productivity grounds, as formerly unemployed workers are judged negatively once on the job, even when we control for on-the-job performance. Across the studies, unemployed workers are perceived not only as less competent but also as less warm. Study 5 is a field study in which fictionalized resumes are sent to real employers. Controlling for qualifications, it finds that discrimination against the unemployed occurs nearly instantaneously to becoming unemployed.

The effects of a teaching intervention on weight bias among kinesiology undergraduate students.

Weight bias is present among kinesiology professionals and this may cause a significant negative impact on their clients with obesity. Thus, our objective was to test if learning about uncontrollable cause of obesity and about weight bias would reduce explicit and implicit weight bias among kinesiology undergraduate students compared to the traditional curriculum which is more focused on controllable causes of weight gain. We recruited undergraduates from two classes of the same kinesiology major course taught by the same instructor. In-class teaching activities consisted of 80 min lecture on day 1, video watching session and a group activity on day 3 for both groups. Intervention group (n = 33) learned about uncontrollable causes of obesity and about weight bias and had activities to evoke empathy. Control group (n = 34) learned the traditional curriculum where they learned the role of exercise and diet in weight management. We measured explicit and implicit weight bias using Anti-Fat Attitude Test (AFAT) and Implicit Association Test (IAT), respectively pre-intervention, immediate post intervention and 1 month later. In mixed model analysis, AFAT Blame scores had significant group by time interaction (p < 0.001). Blame scores significantly reduced with mean differences (standard error (SE)) of -0.35 (0.08) post intervention (p < 0.001) and persisted to be reduced with mean differences (SE) of -0.39 (0.08) even after 4-week follow-up (p < 0.001) only in the intervention group. Odds of having less implicit weight bias was significantly lower at 4-week follow-up than pre-intervention (odds ratio = 0.4; 95% CI: 0.22-0.73) in the control group but no changes were seen in the intervention group. "Blame" component of explicit weight bias significantly decreased when students learned about controllable causes of obesity and weight bias, but implicit bias did not reduce. However, implicit weight bias appears to increase when education on obesity is limited to diet and exercise interventions as taught in the traditional curriculum.

The "hole" story of predatory outer-membrane vesicles.

All Gram-negative bacteria release membrane vesicles. These vesicles contain a cargo of proteins and enzymes that include one or more autolysins. Autolysins are a group of enzymes with specificity for the different linkages within peptidoglycan sacculi that if uncontrolled cause bacteriolysis. This minireview, written in honor and memory of Terry Beveridge, presents an overview of autolytic activity and focuses on Beveridge's important original observations regarding predatory membrane vesicles and their associated autolysin cargo.

Effects of Controllability of Athlete Celebrity Endorsers’ Drug Scandals on Punitive Opinions: Sensation Seeking as a Moderator

Guided by the attribution theory and sensation seeking (SS), this study found that a news article featuring an athlete celebrity endorser’s drug scandal resulting from a controllable cause (e.g., taking performance-enhancing substance) generated stronger punitive opinions, stronger attribution of the scandal to the athlete, and lower sympathy for the athlete. When a news article presented the drug scandal as due to an uncontrollable cause (e.g., taking a medication to relieve a health problem), low sensation seekers had more negative attitudes and were more in favor of punishment than high sensation seekers. Attributions and sympathy were found to be mediators of the interaction effects of controllable versus uncontrollable messages and SS on punitive opinions. This study contributes to research on the attribution theory and SS in the sports communication context and provides practical implications for sports marketers and public relations professionals.

Herbicide ready-mixes effects on weed control efficacy, non-target and residual toxicities, productivity and profitability in sugarcane–green gram cropping system

ABSTRACTWeeds pose a major challenge at the initial stages of sugarcane and when uncontrolled cause high yield losses. This study was undertaken to define a better and cost-effective weed management strategy. We compared ametryn + trifloxysulfuron-sodium (hereafter referred to as trifloxysulfuron) ready-mixes with single applications of trifloxysulfuron, atrazine and 2,4-D for efficacy, non-target and residual toxicities, yield and profitability in a sugarcane–green gram rotation. Results showed that a density of 100 weeds m−2 could reduce sugarcane yield by 18.4 t ha−1. The ready-mix ametryn + trifloxysulfuron (1097.3 + 27.8) g a.i. ha−1 applied 15 days after planting (DAP) caused reductions in weed density by 88.2%, 90.9%, and 90.3%, and weed biomass by 68.0%, 53.8%, and 56.2% compared to unweeded control at 30, 60, and 90 DAP, respectively. Consequently, the sugarcane yield, system productivity, and net returns were increased by 92.1%, 43.5%, and 1515%, respectively due to this ready-mix. It increased system productivity by 23%, 17.2%, and 22.7% compared to trifloxysulfuron, atrazine, and 2,4-D treatments, respectively. This ready-mix may be recommended in sugarcane. This would reduce weed seed bank and herbicide application cost by 50%, and prevent/delay weed shift and resistance.

The Effects of Messages about the Causes of Obesity on Disciplinary Action Decisions for Overweight Employees

ABSTRACTWe investigated the impact of messages about the causes of obesity (controllable or uncontrollable) on the disciplinary action consequences selected for obese employees in response to a work-related mistake. Participants read about either the controllable or uncontrollable causes of obesity before reviewing an ostensible employee file that included a description of an employee mistake. Depending on condition, the file contained a photo of the employee that either depicted them as obese or average weight. Participants were more willing to withhold a raise or promotion from an obese employee than from an average-weight employee. Further, there was little evidence that the messages about the causes of obesity affected participants' perceived control and self-efficacy for healthy behaviors.