The evolution characteristics of the spacial-temporal regional disparity of inbound tourism in Gansu Province
Bibliographic record
Abstract
We toot 14 cities of Gansu province as examples,and decomposed them to three regions of Longdong,Longzhong,Longxi and analyzed the evolution of space-time regional disparity in Gansu province inbound tourism from 1999-2008 by the methods of Standard Deviation,Coefficient of Variation,Theil index and Geographic concentralized index.The results indicated that the development of inbound tourism in Gansu from 1999-2008 was rapid,but overall disparity was still huge,the absolute disparity and relative disparity were very significant,the development of inbound tourism in Gansu province was still extremely imbalanced;The inter-civil disparity gradually diminished,intra-regional gap was larger than that of inter-regional disparity;intra-regional disparity was the main contributor to inter-civil tourism disparity;Most tourism economic centralized in four cities,the space disparity was still large,the development of provincial tourism economy was lack of transition.
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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 | 0.001 | 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 | 0.000 | 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".