Book review: Michael Birch, <i>Mediating Mental Health: Contexts, Debates and Analysis</i>
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
<p dir="ltr">Over the past five decades, there has been an overabundance of research examining the media impact on society and individuals. Mainstream media were often seen contributing to the development of a discursive system, in which underrepresented populations such as those with mental illness are framed with negative themes such as violence and criminality. The National Alliance on Mental Illness (NAMI) in the UK, for instance, alerts us that stigmatizing themes of dangerousness in media representations fuel discrimination and stigma that impact detrimentally on the lives of sufferers (NAMI, 2001). However, research done by health professionals tended to focus predominantly on the media’s negative health impact on ‘patients’, while paying little attention to what the mental illness actually means to those living with mental ill-health and how they shape their identity in relation to media representations.
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 | 0.000 | 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) | 0.003 | 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