Spatial-temporal evolution of village-level commercial activity near newly developed campus:A case study of Jinming Campus,Henan University
Bibliographic record
Abstract
The establishment of the university's new campus exerts important influence on the neighboring village by fueling economic growth,improving villagers' occupation structure,enhancing the economic strength of collectives,and impacting villagers' ideas and behaviors,etc.This paper tries to apply the remote sensing method to the study of commercial business in rural areas.With the help of remote sensing,the phases of economic activities can be obviously observed in near-college villages-the initial changes in system disturbance,rapid growth of commercial activities and the stage of gradual development.The spatial variation of the commercial activities in villages that occurred in different periods is shown on the remote sensing images through the GIS method:(1) The commercial activities extend axially to the inner district of village from the gate of campus living quarter,exhibiting the regularity of distance-decay effect and spatiality.(2) The commercial function of village-level system splits apart gradually,including the high-level variation of commercial operation,division of campus and social space,agglomeration of the commercial space with the same operation.(3) The economic activities assemble on the traffic nodes,spreading statutorily.(4) Commercial operation structure changes regularly with to the development of economy.(5) Shopping trip space for rural residents has the ringed structure of different hierarchies.It is the establishment of Henan University(a comprehensive university) that prompts the population aggregation all of a sudden,turning the western part of Kaifeng into a secondary business centre,which is the primary impetus of the village-level system's economic development.Based on the population growth theory in A-S model and the diversity of consumers' preference in Krugman model,the present paper illustrates the motive of commercial size development,the phenomenon of lasting selection caused by the fact that the agglomeration of population generates the business agglomeration,and the commercial spatial structure development from an unstable disorder to a new stable and orderly condition on a basic regularity as to increasing returns to scale.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".