MétaCan
Menu
Back to cohort
Record W2405724497 · doi:10.1007/s10901-016-9511-8

Establishing stability: exploring the meaning of ‘home’ for women who have experienced intimate partner violence

2016· article· en· W2405724497 on OpenAlexafffund
Julia Woodhall‐Melnik, Sarah Hamilton‐Wright, Nihaya Daoud, Flora I. Matheson, James R. Dunn, Patricia O’Campo

Bibliographic record

VenueJournal of Housing and the Built Environment · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of TorontoPublic Health OntarioSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsDomestic violenceHuman geographyMeaning (existential)Quality of Life ResearchFinancial stabilitySociologyStability (learning theory)PsychologySocial psychologyPoison controlSuicide preventionBusinessPublic healthMedicineNursingEnvironmental healthSocial science

Abstract

fetched live from OpenAlex

There is evidence that involuntary housing instability may undermine health and well-being. For women who have experienced intimate partner violence (IPV), achieving stability is likely as important for other groups, but can be challenging. Through our analysis of 41 interviews with women who have experienced low income and IPV, we argue that definitions of housing stability are multifaceted and for many centred on a shared understanding of the importance of creating an environment of "home". We found that obtaining housing that satisfied material needs was important to women. However, in asking women to define what housing stability meant to them, we found that other factors related to ontological security and the home, such as safety, community, and comfort, contributed to women's experiences of stability. Through our discussion of the importance these women placed on establishing stable homes, we argue that future research on women's experiences with housing stability and IPV should include definitions of stability that capture both material security and women's experiences with building emotionally stable homes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.347
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Housing and the Built EnvironmentSame topicHomelessness and Social IssuesFrench-language works237,207