The Practice Innovation and Standardization Construction of the Assessment for Civil Servant at the Basic Level: Based on the Research of W County in Chongqing
Bibliographic record
Abstract
Strengthening the assessment for civil servant at the basic level is the basis requirements of four comprehensive strategy. This paper empirically studies the practice innovation and standardization construction of the assessment for civil servants at the grass-roots level which takes W county in Chongqing as an example. The study found that: although W county has been established and widely publicized the civil servant assessment system, and achieved remarkable achievement in principles, contents, methods, procedures and results of assessment. but there are still non-standard problems such as the macro and abstract of assessment content, the non-conformance of method using, the lack of openness and feedback of procedure, the results highly concentrated and its use insufficient,etc.. That is because the understanding of assessment purpose and meaning is not clear, the scientific analysis and target management of strategy and position is lack, classified assessment is not scientific and meticulous, and process and standard is neither rigorous nor objective. therefore, this paper puts forward the standardization construction path of the civil servant assessment: to deepen the understanding of evaluation purpose and meaning by strengthen the consciousness education; To establish the reasonable classification grading assessment system by sufficient investigation and scientific research; To determine scientifically the assessment contents and index system through strategic management, target management and position analysis; According to the authority of civil servants and job characteristics, to determine scientifically the assessment main body; To innovate assessment method and technology by perfecting assessment system;To improve the results of the assessment feedback and its use by optimization evaluation procedures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".