In order to provide a comprehensive and objective picture of the state of agricultural development in the counties and to further improve the level of agricultural statistics, the suning county bureau of statistics has maintained a multi-pronged approach through strengtheningOperational trainingHold on tightData qualityStrengthening sectoral collaboration to advance agricultural statistics firmly。
One is to strengthen operational training and upgrade statistical capacity at the grass-roots level. Establishment of a regularized graded training mechanism for the frequent changes in the characteristics of statisticians. On the one hand, intensive training is being strengthened. Annual county-wide operational training sessions on agricultural statistics are held on a regular basis, with systematic rotation of the training of town statisticians around statistical reporting systems, indicator interpretation, data collection methods, etc. On the other hand, on-site guidance is available. In conjunction with the data verification exercise, reaching out to the farm head and the farm house, “one-on-one” guides village-level auxiliary investigators in understanding the meaning of the indicators, regulating the filing process and focusing on the problem of accounting for seasonally strong and diverse agricultural production。
The second is to strengthen auditing and evaluation and to secure data quality thresholds. Make full use of the mandatory audit rules of the statistical cloud platform, conduct real-time monitoring of agricultural production, price and equivalent data, ring fluctuations, enhance scrutiny of trends and compatibility of key indicators, such as food production, cash crop areas, livestock stocking columns, and timely verification of fluctuations。
The third is to strengthen sectoral collaboration and bring together statistical efforts. Regular joint meetings are held with the department of agriculture and rural affairs, the forestry service and others to exchange information on the economic performance of agriculture, study the situation of agricultural production and resolve difficulties and problems in statistical work. At the same time, key data, such as the field where the pig is stored and the area where the crop is planted, are cross-referenced and mutually validated to improve the accuracy of the source data。
