The process of developing a content analysis study to evaluate the quality of breastfeeding information on the Internet-based media
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
The Internet offers a powerful network of information on breastfeeding that is used by doctors, patients, and scientists. The objective of this study is to describe the process of development of a data extraction tool to evaluate the content and quality of breastfeeding information on the Internet. Using a descriptive study method, we examined Internet pages to determine which variables needed to be measured in order to develop the data extraction tool. A purposive sampling of websites was selected to pilot test this tool. The developed data extraction tool has a descriptive structure to characterize websites and text pages. Using the developed tool, we can assess whether the information on text pages is supportive of breastfeeding and whether other strategies that protect breastfeeding are followed. The developed data extraction tool is a useful instrument that can assist researchers in evaluating the quality of information posted on the Internet related to breastfeeding.
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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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