The study demonstrated the level of tax culture as the basis for tax compliance. In turn, the formation of a strong tax culture depended on certain factors. Therefore, there were statements that the degree of such a culture depends on the level of tax communication. To show this connection, this paper analyzed the content of text arrays and products of communicative correspondence by keywords income and asset declaration in the Google search system (content analysis). Results of the analysis demonstrated more than 160 news articles and numerous social media posts. Moreover, the study contains the analytics of social media powered by YouScan artificial intelligence platform. This paper also presents the analysis and results of the sociological survey, in which more than a thousand people participated in the two biggest cities in Kazakhstan. The data of the survey were analyzed by the software Statistica 10 – the statistical data analysis system. The survey showed low tax awareness of citizens, almost 72% of respondents did not know about the introduction of the declaration of income and welfare. The results obviously demonstrated that there is a positive correlation between investigated issues, and poor utilization of information and communications technology by the government. In this way, this paper explored the relationship between tax culture and tax communication, where the awareness of citizens could be a huge step in the formation of honest taxpayers and increase confidence in government institutions.

Floods are among the most frequent and destructive natural hazards in Kazakhstan, particularly in the Abai Region, Kazakhstan, where topographic, hydrological, and climatic factors strongly influence flood occurrence. This study presents a comprehensive spatial assessment of flood susceptibility in the Abai Region using a multi-criteria Geographic Information System (GIS) approach. The analysis integrates twelve flood-conditioning factors representing hydrological, topographic, environmental, and anthropogenic variables. The relative importance of these factors was determined using the Analytical Hierarchy Process (AHP). The results indicate that distance to rivers (20%) and precipitation (16%) are the most influential drivers of flood susceptibility, followed by Height Above Nearest Drainage (HAND) (11%) and drainage density (9%). The resulting flood susceptibility map classifies the study area into five susceptibility levels. Approximately 56.6% of the study area falls within the moderate susceptibility class, while 25.0% is categorized as high susceptibility, mainly concentrated in low-lying floodplains and foothill regions. Low-susceptibility areas account for 18.1% of the region, whereas the very high and very low susceptibility classes together represent less than 1% of the territory. Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis, yielding an Area Under the Curve (ROC–AUC) value of 0.893, indicating strong agreement between predicted susceptibility patterns and observed flood occurrences. Additional validation metrics derived from the confusion matrix show an overall accuracy of 83.3%, precision of 0.75, recall of 1.0, and a Kappa coefficient of 0.67, confirming reliable predictive performance. Sensitivity analysis with ±10% variation in factor weights further demonstrated the spatial stability of the susceptibility results. The resulting susceptibility map provides an important spatial basis for infrastructure planning, flood mitigation, and disaster preparedness in the Abai Region and offers a transferable framework for flood-susceptibility assessment in other semi-arid regions of Central Asia.

With the positive and negative consequences of rapid global urbanization, the main task of the state is to ensure the long-term quality of life of its citizens. Currently, reforms undertaken by post-Soviet states aimed at environment-related projects are facing increasing resistance and protest from local populations. In 2020, the authors of this paper carried out a study on the Maly Taldykol lake group, located in the south-western planning region of Nur-Sultan. The purpose of this work wasto conduct an assessment of ecosystem services to inform effective management decisionsin urban planning. A strategy of combined research methods was applied. Because of the lack of data, the challenge was to explain, summarize, and verify the data obtained by one method through the application of another method. Analysis of the data showed that the annual costs associated with the creation of artificial “islands of nature” through the expansion of green areas is 20 times less than the losses associated with the development of the territory of Maloe Taldykol and the consequential loss of natural landscape. The results revealed that keeping these ecosystem services in their natural setting reducesthe cost of providing these services in an alternative way, and avoids the negativeimpact of an ill-conceived decision. The uniqueness of this interdisciplinary study lies in thecost-benefit analysis of the findings of the assessment of ecosystem services, which result inthe most effective management decisions in urban planning. Keywords: public management, ecosystem approach, urban planning, ESVD

Accurate and repeatable assessments of dairy cattle body conformation are essential for productivity, welfare monitoring, and selective breeding. While 3D imaging technologies offer promising alternatives to manual measurements, the performance of low-cost, open-source solutions, such as Kinect 2.0 and OAK-D, remains insufficiently validated under farm conditions. This study assessed the accuracy and agreement of Kinect 2.0 and OAK-D cameras compared with manual caliper-based measurements in 41 dairy cows. Six key exterior traits—three vertical (withers, back, and stature) and three horizontal (chest depth, hook width, and loin width) traits—were measured. Linear regression and Bland–Altman analyses were used to evaluate agreement. OAK-D outperformed Kinect 2.0 in horizontal traits, with regression slopes of 0.908–0.976 and R² values of 0.58–0.61, and showed minimal systematic bias (–0.11 cm; LoA ±3.3 cm). Kinect 2.0 performed better in the vertical dimension (R² up to 0.85) but failed in terms of body depth (R² = 0.016), with a wide LoA (±15.3 cm). The results support the application of the OAK-D for automated exterior scoring in dairy cattle. Its affordability, open architecture, and compatibility with AI underscore its strong potential for scalable, farm-adapted, multiangle systems in precision livestock management.

Kazakhstan’s 2025 Water Code aims to institutionalize Integrated Water Resources Management (IWRM), but its success is threatened by a persistent “implementation gap” between policy requirements and the workforce’s practical competencies. This study provides empirical evidence of a persistent misalignment between water-related higher education and emerging governance demands in Kazakhstan by conceptualizing the implementation gap as a human-capital deficit. We conducted a repeated two-wave survey of students enrolled in “Water Resources” programs (n₁ = 39, n₂ = 82) to empirically diagnose this gap and examine changes in educational preferences over time. The findings reveal an overwhelming demand for dual education (97.6%), alongside a statistically significant shift (χ²(1) = 33.53, p < 0.001) from theory-oriented learning (56.4% to 4.9%) toward practice-oriented formats (30.8% to 62.2%). Key reported constraints include limited access to modern laboratories (47.6%) and insufficient real-world professional experience (28%). Taken together, these results indicate a structural misalignment between academic training and the competency requirements implied by ongoing water-sector reforms. The study concludes that dual education may function as an institutional mechanism for narrowing the policy-to-competence gap, supporting efforts to operationalize the 2025 Water Code and advance Sustainable Development Goals 4 and 6.