Navigating the maze: understanding the information journeys of women in second-stage shelters
Bibliographic record
Abstract
In this study, we explored the complex information journeys of women residing in second-stage shelters in Alberta, Canada, using a grounded theory approach. Analysis of detailed interviews with 20 participants who have experienced intimate partner violence (IPV) uncovered the multifaceted challenges women faced as they navigated the interconnected systems of legal, financial, housing, and social support services. The theory generated was navigating the maze, which aptly reflected their experiences, highlighting the barriers and facilitators encountered along the way to obtaining information critical to their decision-making about their lives. Five key themes were identified: the Elusiveness of Entry, the Full-Time Job of managing support systems, the My home – their ‘house rules’: tensions between individual needs and shelter rules, Endless Corridors of decision-making, and the Shared Wisdom among residents. The researchers emphasized the need for greater clarity, support, and equity within the shelter system to better assist women in their journey towards independence and safety. These findings have significant implications for policy and practice, advocating for a more transparent and supportive approach to second-stage shelters.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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 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".