A method to test the significance of differences between centrographic measures of dispersion
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Centrographic measures of spatial dispersion, such as the standard distance, provide a numerical value to summarize the radial scattering of a set of points around their centre of gravity or centroid. This paper develops a procedure to test for the statistical significance of differences in dispersion between two sets of phenomena intertwined in space. The significance test is implemented using a resampling randomization procedure based on the pooled locations from both sets to estimate the sampling distribution of their differences. Repeated thousands of times, that yields empirical frequency thresholds of the sampling distributions to assess the statistical significance of the observed differences. Case studies based on residential locations of lone‐parent families and retired couples in the Quebec City Metropolitan Area illustrate the procedure. This paper shows how randomization procedures can be used to adapt classical tests to assess the statistical significance of differences between indices of spatial dispersion.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it