Western Galilee College

Statistical literacy is widely regarded as a core competency for academic achievement and informed decision-making across disciplines. However, many students experience elevated statistics anxiety and hold negative attitudes toward statistics, which can hinder their learning outcomes. The purpose of this study was to investigate differences between students with and without learning disabilities (SLD) and/or attention deficit hyperactivity disorder (ADHD) in statistics anxiety, attitudes toward statistics, and statistical literacy, and to examine the mediating role of attitudes in the relationship between statistics anxiety and statistical literacy. A total of 405 higher education students participated: 44 students with SLD/ADHD, 50 students with only-ADHD, and 311 without SLD/ADHD. Participants completed the Hebrew statistical anxiety rating scale and a statistical literacy assessment. Results showed that students with SLD/ADHD experienced higher levels of statistics anxiety and less favorable attitudes toward statistics compared to students without SLD/ADHD. Computational self-concept emerged as a significant mediator between test and class anxiety-a component of statistics anxiety-and statistical literacy for students with SLD/ADHD. The study highlights the importance of addressing both attitudinal and anxiety factors in statistics education for students with SLD/ADHD, as well as the need for targeted interventions to foster statistical literacy in higher education.

Philanthropic activity has become central within neoliberal welfare states. Philanthropic organisations serving marginalised Jewish communities in Israel are investigated through semi-structured interviews with twenty-three founders and senior leaders from ultra-Orthodox and immigrant communities. Three organisational types are identified: cultural enclave organisations that preserve group distinctiveness while avoiding cooperation with governmental actors; socially incorporating organisations that seek mainstream integration; and hybrid organisations that balance both approaches. These types systematically differ in their motives for establishment, intentions, aims, beneficiaries, community environment, and governmental interface. Beyond classification, the resulting typology suggests that organisational formation reflects an interaction among identity and belonging logics, multidimensional marginality, and institutional opportunity structures that shape state-third-sector engagement under welfare retrenchment. This research offers a meso-level perspective for understanding how marginalised communities institutionalise philanthropy and, in doing so, negotiate their relationship with state institutions.

Confirmation and intergroup biases significantly influence legal decision-making, particularly in evaluations of evidence and credibility. While prior research has examined ethnicity and criminal history separately, little is known about their interaction in shaping perceptions of eyewitness effectiveness. In this study, 324 Israeli-Jewish participants assessed an eyewitness—either Israeli-Arab or Israeli-Jewish—with or without a criminal record. Drawing on social identity theory, we hypothesized that in-group eyewitnesses would be evaluated more favorably than out-group eyewitnesses, particularly when a criminal record was present. Contrary to this prediction, Israeli-Arab eyewitnesses were rated as more effective than Israeli-Jewish eyewitnesses. A significant interaction revealed that Israeli-Jewish eyewitnesses with a criminal record were perceived as less effective than their Israeli-Arab counterparts, whereas no ethnic differences emerged when no record was present. Findings highlight the joint influence of intergroup dynamics and criminal history, and underscore the need for future replication using more ecologically valid and diverse methodologies.

This paper examines whether information-theoretic complexity measures enhance industry-group return forecasting and portfolio construction within a machine-learning framework. Using daily data for 25 U.S. GICS industry groups spanning more than three decades, we augment gradient-boosted decision tree models with Shannon entropy and fuzzy entropy computed from recent return dynamics. Models are estimated at weekly, monthly, and quarterly horizons using a strictly causal rolling-window design and translated into two economically interpretable allocation rules, a maximum-profit strategy and a minimum-risk strategy. Results show that the top performing strategy, the weekly maximum-profit model augmented with Shannon entropy, achieves an accumulated return exceeding 30,000%, substantially outperforming both the baseline model and the fuzzy-entropy variant. On monthly and quarterly horizons, entropy and fuzzy entropy generate smaller but robust improvements by maintaining lower volatility and better downside protection. Industry allocations display stable and economically interpretable patterns, profit-oriented strategies concentrate primarily in cyclical and growth-sensitive industries such as semiconductors, automobiles, technology hardware, banks, and energy, while minimum-risk strategies consistently favor defensive industries including utilities, food, beverage and tobacco, real estate, and consumer staples. Overall, the results demonstrate that entropy-based complexity measures improve both economic performance and interpretability, yielding industry-rotation strategies that are simultaneously more profitable, more stable, and more transparent.

PurposeTo examine the association between the type of locality members of ethnonational minority reside in and their willingness to cooperate with police, as measured by the extent of their readiness to report victimization and witnessed crime to this institution. The social capital perspective served as the study's theoretical framework.Design/methodology/approachData were obtained from the Personal and Community Security Index Survey conducted among the Arab citizens of Israel in 2020 (N = 1,004). The data were analysed using linear regression models.FindingsResidents of ethnically mixed localities exhibited greater willingness to report victimization as compared to residents of ethnically homogeneous localities. In contrast, residents of ethnically mixed localities exhibited lower willingness to report witnessed crime as compared to residents of ethnically homogeneous localities.Research limitations/implicationsThe results are in line with the social capital perspective. They suggest that residing in localities of different ethnic composition corresponds to varying levels of social cohesion and mobilization of various social capital types to preserve social order, resulting in a varying extent of willingness to cooperate with the police.Originality/valueThis is one of the first studies attempting to link between ethnic composition of residential localities and the willingness to cooperate with police.