No Such Effect? The Implications of Measurement Error in Self-Report Measures of Mobile Communication Use
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
Research on the social and psychological effects of mobile phone communication primarily is conducted using self-report measures of use. However, recent studies have suggested such measures of mobile phone communication use contain a significant amount of measurement error. This study compares the frequency of mobile phone use measured by self-report questions with error-free log data automatically collected through an Android smartphone application. Using data from 310 Android phone users in Japan, we investigate the extent to which nonrandom measurement error exists in self-report responses to questions about mobile phone use and predictors of this error. Our analysis shows that users generally overreport their frequency of mobile communication and that overestimation is better predicted by proxy measures of social activity than demographic variables. We further show an example of how overreporting can result in an overestimation of the effects of mediated communication on civic engagement. Finally, the value of behavioral log data in mediated communication research is discussed.
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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 | 0.022 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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