Voices from the survey margins: Investigating unsolicited comments written in children’s activity-travel diaries
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
While digitally recording data from hardcopy activity-travel diaries, a team of transportation and health researchers noticed the presence of unsolicited comments on the survey documents. While an immense body of work has been amassed about survey design and analysis, transport scholars have not written about the presence of unsolicited feedback in activity-travel diaries. This paper reports on a thematic analysis of the unsolicited comments written within activity-travel diaries. Two key themes were identified: data quality and respondent affect. Comments about data quality pointed toward possible measurement error due to difficulties incorporating the study into everyday life, or due to human-error. Respondents also offered some additional context for reported data. Affective responses included apologizing for possible data errors and expressions of frustration with the survey. Most respondents who wrote unsolicited comments self-identified as female, of higher education, and employed full-time. The presence of unsolicited comments offered a unique window into the research experiences of the researched, questions and comments raised by participants point toward possibilities in terms of survey design and future research.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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