Multi-agency management of a World Heritage Site: Wulingyuan Scenic and Historic Interest Area, China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Involving a variety of stakeholders, heritage tourism management requires a collaborative multi-actor approach. Due to the current grid management system, shared management among multiple agencies is not rare in heritage sites in China; however limited research has addressed this situation. A multi-agency management model is thus proposed to highlight the roles of a coordination agency and a collaboration mechanism. Taking Wulingyuan Scenic and Historic Interest Area as an example, this paper compares the management status and assesses management collaboration between its two main management bodies. Semi-structured interviews with management staff are used as the primary research method. It is revealed that shared management has resulted in the inefficient use of human and financial resources, and inconsistency in the application of management measures and standards due to the lack of an efficient coordination agency and collaboration mechanism. Suggestions are made to facilitate collaboration and enhance management efficiency in this multi-agency management context.
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.
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 | 0.001 | 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) | 0.001 | 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 it