Depression Is to Diabetes as Antidepressants Are to Insulin: The Unraveling of an Analogy?
Bibliographic record
Abstract
The common comparison of depression to diabetes enables the construction of depression as a nonstigmatizing chronic illness that requires medication. We explore, through the use of discourse analysis, how both long-term users of antidepressants and family physicians invoked this analogy in research interviews. Specifically, we show how these participants explicitly or implicitly challenged the aptness of the depression-diabetes analogy as framed either within a generic (and presumably type 1) conception of diabetes or within the model of type 2 diabetes. These challenges include demonstrating how the elements or inferences of the analogy do not correspond, and how the analogy does not have its intended effects. We consider the implications of the unraveling of this analogy for the construction of depression as a chronic medical condition, for the supposed ease of prescribing and taking antidepressants, and for the reduction of stigma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.006 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".