Bibliographic record
Abstract
With arrivation of age population times and requestion of the social security system perfected gradually, our country functionary retirement system of public official already shows a lot of abuse now. This article thinks that the public official is the peculiar occupation group, whose endowment insurance responds to road of visiting social insurance. Key words: endowment insurance, public official, retirement Résumé: Avec le vieillissement de la population et la demande du perfectionnement du système d’assurance sociale, se sont manifestés des inconvénients du système de retraite des fonctionnaires en vigueur de notre pays. Après l’analyse, l’auteur pense que les fonctionnaires sont un groupe professionnel spécial, dont l’assurance¬ vieillesse doit prendre la voie de l’assurance sociale. Mots-clés: assurance-vieillesse, fonctionnaires, retraite 摘è¦ï¼šéš¨è‘—人å£è€é½¡åŒ–時代的到來和é€æ¼¸å®Œå–„社會ä¿éšœåˆ¶åº¦çš„è¦æ±‚，我國ç¾æœ‰çš„公務員退休制度已顯露出 眾多弊端。本文在經éŽåˆ†æžå¾Œèªç‚ºï¼Œå…¬å‹™å“¡ä½œç‚ºç‰¹æ®Šçš„è·æ¥ç¾¤é«”，其養è€ä¿éšªæ‡‰èµ°ç¤¾æœƒä¿éšªä¹‹è·¯ã€‚ é—œéµè©žï¼šé¤Šè€ä¿éšªï¼›å…¬å‹™å“¡ï¼›é€€ä¼‘
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
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".