Comparison of the Quality of Qualitative Data Obtained through Telephone, Postal and Email Surveys
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
Many claims have been made about the advantages of conducting surveys on the web. However, some concerns have been raised about the quality of the information gathered through this medium. The purpose of this research was to compare the quality of qualitative information obtained using three datacollection methods, in the context of the development of a scale for the measurement of corporate image. First, a study was carried out to generate a list of items that could be used to describe all elements of the corporate image of three firms as perceived by consumers. Different lists of items were obtained from telephone, postal and web-based surveys. Next, a qualitative study was conducted to assess the predictive validity of the lists of items obtained from each data-collection method. The results showed that the quality of qualitative data obtained through a web-based survey was comparable to that of information obtained through telephone and postal surveys, for two of the three target firms.
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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 | 0.085 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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