Retail Preferences Survey Report
Bibliographic record
Abstract
The purpose of this survey is to determine how many Lawrence residents intentionally leave Lawrence to shop, what percentage of their total shopping dollars they spend outside Lawrence, what types of goods or services they look for, where they go to shop, and how often they go there. \n \n \nThe survey was limited to Lawrence residents and does not measure the impact or preferences of visitors coming into the city of Lawrence for the purpose of shopping. \n \n \nAn attempt was made to identify those stores, retail centers, and types of items or services for which shoppers consider an out-of-town source their first/best choice, and the reasons for that choice. \n \n \nThis is the fourth time this survey has been conducted. Comparisons are made throughout regarding the changes from the previous sampling. This year in an attempt to provide a sample of population that will cover all groups of population better the data were collected in two samples: between Thanksgiving and Christmas 1999 and in the second part of January 2000, after students had come back from the Christmas break. In the future survey data will be collected in January, following the Christmas shopping season.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 0.033 |
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".