With the development of teaching reform, how to optimize funding and education activities from the perspective of "Great Ideological and Political Education" and improve accuracy has become a focus. From the analysis of the current teaching development situation, the guiding role of ideological and political education in funding precision education activities has been very obvious. To better enhance the effectiveness of funding education, actively optimize the precision of funding education, and innovate the way related activities are carried out, which is an inevitable choice for better education work. Based on this, this article mainly studies the precise methods of funding education under the perspective of "Great Ideological and Political Education", for reference only.

This study thoroughly examined the use of different machine learning models to predict financial distress in Indonesian companies by utilizing the Financial Ratio dataset collected from the Indonesia Stock Exchange (IDX), which includes financial indicators from various companies across multiple industries spanning a decade. By partitioning the data into training and test sets and utilizing SMOTE and RUS approaches, the issue of class imbalances was effectively managed, guaranteeing the dependability and impartiality of the model’s training and assessment. Creating first models was crucial in establishing a benchmark for performance measurements. Various models, including Decision Trees, XGBoost, Random Forest, LSTM, and Support Vector Machine (SVM) were assessed. The ensemble models, including XGBoost and Random Forest, showed better performance when combined with SMOTE. The findings of this research validate the efficacy of ensemble methods in forecasting financial distress. Specifically, the XGBClassifier and Random Forest Classifier demonstrate dependable and resilient performance. The feature importance analysis revealed the significance of financial indicators. Interest_coverage and operating_margin, for instance, were crucial for the predictive capabilities of the models. Both companies and regulators can utilize the findings of this investigation. To forecast financial distress, the XGB classifier and the Random Forest classifier could be employed. In addition, it is important for them to take into account the interest coverage ratio and operating margin ratio, as these finansial ratios play a critical role in assessing their performance. The findings of this research confirm the effectiveness of ensemble methods in financial distress prediction. The XGBClassifier and RandomForestClassifier demonstrate reliable and robust performance. Feature importance analysis highlights the significance of financial indicators, such as interest coverage ratio and operating margin ratio, which are crucial to the predictive ability of the models. These findings can be utilized by companies and regulators to predict financial distress.

The theoretical framework of Production Oriented Approach (POA) proposed by Professor Wen Qiufang has undergone a series of development and improvement, forming a "drive facilitate evaluate" teaching framework system that is guided by output tasks, supported by facilitation activities, led by teachers, and jointly constructed by teachers and students. The "facilitation" link is the core of helping learners achieve goals and achieve output tasks. Based on the ideas and requirements of this theory, the author has designed a series of "facilitation" activities to be applied in advanced English reading classrooms. This article intends to review and reflect on these teaching practice activities, in order to gain a deeper understanding of POA theory.

Vocational colleges should not only cultivate highly skilled talents, but also improve the comprehensive quality of students. The cultivation of students' comprehensive qualities cannot be separated from the efforts of schools, counselors, and every course teacher. Vocational education is different from undergraduate education, and finding a teaching model suitable for students in vocational colleges is particularly important. The integrated teaching model proposed in this article integrates theory and practice, and the entire teaching process is integrated into curriculum ideological and political education. In order to ensure teaching effectiveness, teachers participate and supervise the entire process, aiming to cultivate students' ability to unite and assist, solve problems, and express language skills, self-learning abilities, etc., so that students can truly become a comprehensive and high-quality talent.

Interest in the impact of environmental innovations on firms’ financial performance has surged over the past two decades, but studies show inconsistent results. This paper addresses these divergences by analyzing 74 studies from 1996 to 2022, encompassing 4,390,754 firm-year observations. We developed a probability-based meta-analysis approach to synthesize existing knowledge and found a generally positive impact of environmental innovations on financial performance, with a probability range of 0.85 to 0.97. Manufacturing firms benefit more from environmental innovations than firms in other industries, and survey-based studies report a more favorable relationship than those using secondary data. This study contributes to existing knowledge by providing a comprehensive aggregation of data, supporting the resource-based view (RBV) and the Porter hypothesis. The findings suggest significant policy implications, highlighting the need for tailored incentives and information-sharing mechanisms, and underscore the importance of diverse data sources in research to ensure robust results.