Research on the Priority of County-Level Territorial Space Consolidation: Form–Flow Synthesis Analysis Based on Principal Component Analysis
Bibliographic record
Abstract
The scientific identification of the priority of territorial space consolidation in counties is a key prerequisite for clarifying the direction of regional improvement and implementing differentiated spatial governance strategies. This paper breaks through the traditional evaluation paradigm of separating “form” and “flow”, and for the first time innovatively integrates the theory of “form–flow synthesis” with the method of principal component analysis. This paper takes Deqing County as the empirical study area. Through principal component analysis, 19 initial indicators were dimensionally reduced into a “flow–form” two-dimensional space with clear geographical significance. Then, the natural discontinuity method was used to classify it into nine types of “flow–form” combination types, and the 13 towns of Deqing County were projected onto the “flow–form” two-dimensional coordinates, thereby objectively revealing the matching/mismatch relationship between the “flow” and “form” in space. The results show that the current territorial space of Deqing County presents characteristics of “overall balance but local imbalance”. This paper also discusses the consolidation priority strategy based on the “flow–form” matching results.
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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 | 0.002 |
| 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) | 0.001 | 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 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".