Behavioral Clustering of the Cell Phone Users in Various Country Markets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Acknowledging Aoki and Downes (2003) cell phone behaviours, the significance of social ecological models and behavioural clustering, the existence of inter-market behavioural clusters in Finland, UAE, China, Canada and New Zealand were investigated. There were significant differences in the cell phone behaviours between the different age groups (in 19 out of 30 variables), genders (20/30) and different countries of residence (30/30) implying that these variables could be used as distinguishing variables regarding the existence of the cell phone behavioural clusters. This implies that the variables age, gender and country of residence do not efficiently discriminate the sample population in terms of the cell phone behaviour. Finally, the behavioural variables were used as the cluster variate in order to discover more viable cluster (segments) in the data set. The paper concludes with a discussion regarding the academic and managerial implications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| 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