“If You’re a Parasite, Then You’re Not Normal”
Bibliographic record
Abstract
Previous research in sociology has shown that what is considered as sanity or mental health is described according to a social ideal. Mental health problems have been theorized as a deviance from such norms. Depression, in particular, has been the object of sociological contemplation due to its divergence from a Western social normativity focused on functionality, adaptation and productivity. This research adds to this body of work on depression as a deviation from social norms. It seeks to address a gap within the literature, by exploring the ways in which the “post-depressive” state may be defined in accordance with social norms. As such, it analyzes the links between “post-depression” and normality, from the perspective of individuals having lived with depression. 46 semi-structured interviews were conducted with Canadians individuals who have experienced depression. Results from our content analysis show that the absence of depression was often synonymous with normality and characterized by the following dimensions: a positive attitude; the potential to take action; functionality and performance; self-management; a positive relationship with others; and the notion of meaningful projects. Our results show that participants do not define the absence of depression following psychiatric or clinical indicators, as recorded in the DSM, and that they do not consider it to be a return to an anterior, pre-depression, state. Rather, post-depression is idealized, perceived as a state of unfailing conformity to social expectations and norms.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".