Paper and plastic in daily diary research: Comment on Green, Rafaeli, Bolger, Shrout, and Reis (2006).
Bibliographic record
Abstract
The authors applaud A. S. Green, E. Rafaeli, N. Bolger, P. E. Shrout, and H. T. Reis's (2006) response to one-sided comparisons of paper versus electronic (plastic) diary methods and hope that it will stimulate more balanced considerations of the issues involved. The authors begin by highlighting areas of agreement and disagreement with Green et al. The authors review briefly the broader literature that has compared paper and plastic diaries, noting how recent comparisons have relied on study designs and methods that favor investigators' allegiances. The authors note some sorely needed data for the evaluation of the implications of paper versus plastic for the internal and external validity of research. To facilitate evaluation of the existing literature and assist in the design of future studies, the authors offer a balanced comparison of paper and electronic diary methods across a range of applications. Finally, the authors propose 2 study designs that offer fair comparisons of paper and plastic diary methods.
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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 | 0.019 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.046 | 0.046 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".