Hard or Soft Searching? Electronic Database Versus Hand Searching in Media Research
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
It is important for qualitative media researchers to consider the impact of their research objectives on the sample frame imposed and subsequent data-collection methods. To illustrate this, we present some of the issues we encountered in determining a method of gathering physical activity articles in daily newspapers. We consider the implications of search choices for our sample, highlight the impact of using hardcopy hand-searches and electronic indexes and emphasise the importance of conducting a study to determine the reliability of hand-searching versus electronic index search methods. We suggest that researchers should be aware of the benefits and drawbacks of search methods including what kinds of information these methods yield and the possible effects on the research project. We conclude by highlighting the importance of these discussions to the reliability of content analysis. URN: urn:nbn:de:0114-fqs0703204
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 | 0.036 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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