Modern International Park City and Ecological Civilization Education Practice: Taking Chengdu Tianfu Greenway as the Core
Bibliographic record
Abstract
In the comprehensive development of modern park city and ecological civilization education, Chengdu has gradually explored its own path with international characteristics. The positioning of Chengdu as a “modern and beautiful park city” is an innovation proposed by Mr. Xi Jinping in recent years. This concept not only combines the geographical location of Chengdu with the regional characteristics of the western environment, but also highly respects the historical laws of the development of Chengdu’s Bashu civilization for thousands of years. At the same time, it also absorbs Howard’s “pastoral city” dream and Mountford, the theme of Gedde’s “Organic City Theory” has corrected the shortcomings of Le Corbusier’s mechanized functional space view and presented distinctive Chinese characteristics in theoretical innovation and the development of ecological civilization education. The outstanding performance is the organic integration of the development of Tianfu ecological civilization, the cultural education of Bashu and the aesthetic design practice, the creation of the international brand image of Chengdu’s “three cities and three capitals” and the innovative practical experience results of the dream of “beautiful and livable park city”.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".