Bibliographic record
Abstract
Living in a world of television, computer games, and a visual online world, children and books become more distant. Reading habits of the next generation determine the future of the nation. Many nations in the world promote a reading environment, raising reading ability as policy priority. The Kaohsiung Public Library has been the landmark of effortful and proactive promotion of reading in southern Taiwan. In recent years, in order to complement school education, and raise national competency, the Kaohsiung Public Library has, based on the principal of “Customer Center, Proactive and Progressive”, reached out to numerous campuses, providing diversified services to promote and raise the level of literacy of school children. Mayor Ju-lan Ye, a great enhancer and promoter of reading, in addition to founding the “Reading with the Mayor: the Chrysanthemum Reading Club” to read with under-privileged groups, has added 5,000,000 NT dollars to the originally allocated budget for the purchase of books for elementary and middle schools to enrich the library collections. Through the various strategies to promote children’s reading, the Kaohsiung Public Library has disseminated the seeds for reading in every corner of campuses where students can read and enrich their lives in the world of books.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".