In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

This article evaluates the Didactic Strategies for Teaching Mathematics (DSTM) program, designed to enhance the teaching of mathematical content in primary and secondary education in a hybrid modality. In alignment with SENACYT’s Gender-STEM-2040 Policy, which emphasizes gender equality as a foundational principle of education, this study aims to assess whether initial teacher training aligns with this policy through the use of mathematical strategies promoting gender equality. A descriptive-correlational approach was applied to a sample of 64 educators, selected based on their responses during the training, with the goal of improving teaching and data collection methodologies. Findings indicate that, although most teachers actively engage in training, an androcentric approach persists, with sexist language and a curriculum that renders girls invisible, hindering the fulfillment of the National Gender Equality Policy in Science, Technology, and Innovation of Panama (Gender-STEM Policy 2040). Additionally, through a serendipitous finding, a significant gap in student activity levels, especially in secondary school, was discovered. While in primary school, activity levels were similar between genders, a decline in active participation among girls in secondary school was observed. This discovery, not initially contemplated in the study’s objectives, provides valuable insights into gender differences in active participation, particularly in higher educational stages. The serendipity suggests the need for further exploration of social, environmental, and family factors that may influence this decrease in girls’ active participation. The article concludes with a preliminary diagnosis and a call to deepen gender equality training and the effective implementation of coeducation in Panama’s educational system.

This study examines the financial integration between Jordan and the BRIC economies (Brazil, Russia, India, and China) to determine whether long-term equilibrium relationships exist and to assess implications for portfolio diversification and policy. Drawing on daily stock index data from 01 January 2014, to 31 August 2024, the study employs econometric techniques, including Granger Causality tests, Johansen Cointegration, and Vector Autoregression (VAR). The stationarity of stock indices at the first difference level is confirmed through unit root testing. Results indicate minimal long-term cointegration between Jordan and BRIC markets, pointing to low integration and potential diversification benefits for institutional investors. However, short-term causal links—particularly between Jordan and the Russian and Indian markets—highlight these countries’ influence on Jordan’s stock fluctuations. The findings suggest that, in the absence of long-term cointegration, investors may mitigate risk by investing in less correlated markets, such as Jordan, while leveraging short-term partnerships with Russia and India. Additionally, the study provides valuable insights for business leaders considering strategic alliances with BRIC counterparts in sectors like technology, agriculture, and energy, and calls for future research into factors like regulatory frameworks and geopolitical stability that may limit long-term financial integration. These results have significant implications for institutional investors, business executives, and policymakers, suggesting targeted strategies for financial stability, risk mitigation, and economic collaboration.

This research study aims 1) to create a structural equation model for sports sponsorship of halal products in Thailand and 2) to examine the direct and indirect influence of variables that are components of the structural equation model for halal products, specifically in the context of becoming a sports sponsorship for halal products in Thailand. The study focused on a sample group of Thai Muslims interested in watching and following the news and participating in Thai sporting events. The researcher chose a sample size of 400 participants from this population, excluding backup data gathering and data analysis, to ensure the questionnaire’s quality and dependability. The results of the data analysis from the structural equation model created show that it is consistent with empirical data. The results of the statistical hypothesis test reveal that the level of religious adherence and the level of awareness of entering into sponsorship have both direct and indirect influences on consumer attitudes and purchase intentions with statistical significance at 0.01. It can also be identified that if a sponsor increases awareness among Muslim viewers through branding or product presentations in events that feature halal symbols or indicate compliance with religious standards, it will lead to a more positive attitude and higher purchase intentions. This insight can be applied to marketing promotion in administrative regions or countries where the majority of the population is Muslim.

The study has formulated the objective of synthesizing the extent to which technological barriers intervene in the transparency and effectiveness of public management (PM). Methodologically, the study was of a fundamental or basic nature, with a systematic review design, the databases of Scopus (369), SciELO (2), Web of Science (184) were explored, after the review process a set of 22 articles was available. The registration was made in an Excel table where the main data of the articles were included. 32% of the articles selected for the analysis of the evidence are from the period 2020, 27% were from 2022 and 18% from the year 2023; as far as origin is concerned, 14% of the articles come from Peru and 9% from Australia, Brazil, South Korea, Spain and Indonesia. In summary, the study points out that government institutions are making progress in digitizing and improving the citizen experience through electronic services, but they face challenges in areas such as resource management, the low adoption of advanced technologies such as blockchain and artificial intelligence, as well as the lack of transparency in PM. Despite this, it is highlighted that e-government improves citizen satisfaction, and the need to invest in digital innovation, training and overcoming technological barriers to achieve an effective transformation in state administration and promote a more inclusive and advanced society is emphasized.

In this study, the author investigates the evolving role of women in corporate boardrooms historically dominated by men, aiming to discern whether their inclusion merely serves as symbolic representation or carries substantive impact. Using a narrative literature review methodology, the author meticulously examines the historical impediments women faced in leadership positions. The findings suggest that deep-seated societal biases, rather than a lack of capability, traditionally constrained women’s leadership trajectories. While some studies suggest that corporations with genuine gender diversity in leadership may outperform in financial outcomes and innovation, this advantage is not consistently observed across all contexts and industries, necessitating a cautious interpretation of these mixed and context-dependent findings. The study argues that women’s inclusion in boardrooms is a strategic imperative for modern corporations striving for resilience, adaptability, and sustained growth in an intricate global landscape, yet also recommends further research to fully understand the broader impacts of such diversity. Furthermore, the study offers practical strategies for enhancing gender diversity in corporate leadership.