Compression: The Basic Psycho-Social Problem in Managing Health Among Women with Suicide Ideation
Bibliographic record
Abstract
Suicide ideation (SI) exceeds combined rates of suicide attempts and deaths yet is vastly overlooked in the literature. Understanding SI is crucial for supporting those who live with these thoughts, particularly women, who experience higher rates of SI than men. Women seeking support are not necessarily looking for help with their SI, rather, their health problems and general wellness. For this reason, we used a Glaserian grounded theory approach to understand the strengths and barriers of how women with SI manage or promote their health. Thirty-two women from four Canadian provinces with SI were interviewed. Data was analyzed using a constant comparison method. Using a Glaserian approach, analysis renders an emergent central variable, and findings are written conceptually instead of descriptively. Findings yielded a theoretical rendering of the basic psycho-social problem (central variable) and process of managing or promoting their health. Here, we report on the psycho-social problem, identified as compression, the sense of being squeezed out of social spaces due to others’ rejection of SI. Compression involves feeling pressured to end SI and to prioritize others’ needs above their own, imposing demands on women to remain alive and sustain a high level of functioning. Trauma and violence informed approaches are essential to reduce compression, by offering spaces where women are free to discuss SI and how to manage psychological pain with others.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".