Training Course for Guizhou Teachers for the Establishment of Schools Libraries
Bibliographic record
Abstract
In the past two decades, under the economic reform, in The Mainland China, the annual economic growth(GDP) is more than 10%, but in general ,in the western part of China most of the people are lived in poverty and uneducated. As a result, there are lots voluntary and charitable agencies in Hong Kong which help the Chinese people to get rib of poverty and let the kids in the villages receive education. They support the rural area to build schools and set up school libraries in order to enhence the educational standard in the rural area. In December, 2006, the Hong Kong Teacher-librarians’ Association was invited by the JIAN XING CHARITABLE FOUNDATION LIMITED, one of the charitable agencies to organise a four and a half days training course for the school teachers in Guizhou province, who will be responsiblefor the operation of the school libraries in future. With the help of the Jiangsu provinces Mr. Cheung Jing Wo, the course was successfully helded in Jin Sha of the Guizhou province.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.227 | 0.052 |
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".