Logistics Sprawl: Differential Warehousing Development Patterns in Los Angeles and Seattle
Bibliographic record
Abstract
The warehousing industry experienced a period of rapid growth from 1998 to 2009. This paper compares how the geographic distribution of warehouses changed in both the Los Angeles and Seattle Metropolitan Areas over that time period. These two west coast cities were chosen due to their geographic spread and proximity to major ports as well as their difference in size. The phenomenon of logistics sprawl, or the movement of logistics facilities away from urban centers, which has been demonstrated in past research for the Atlanta and Paris regions, is examined for these two areas. The weighted geometric center of warehousing establishments was calculated for both areas for both years, along with the change in the average distance of warehouses to that center, an indicator of sprawl. We find that between 1998 and 2009, warehousing in Los Angeles sprawled considerably, with the average distance increasing from 25.91 to 31.96 miles, an increase of over 6 miles. However in Seattle, the region remained relatively stable, showing a slight decrease in average distance from the geographic center. Possible explanations for this difference are discussed.
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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 | 0.001 |
| 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".