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Record W2256363758 · doi:10.1111/sjop.12254

Beliefs about intimate partner violence: A survey of the Swedish general public

2015· article· en· W2256363758 on OpenAlexaboutno aff
Helen Alfredsson, Karl Ask, Chris von Borgstede

Bibliographic record

VenueScandinavian Journal of Psychology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsDomestic violenceBlamePsychologyPsychological interventionIntervention (counseling)Injury preventionSuicide preventionPoison controlQuarter (Canadian coin)Human factors and ergonomicsSocial psychologyDemographyPsychiatryMedicineEnvironmental healthGeographySociology

Abstract

fetched live from OpenAlex

Public interventions are considered to be an important means of preventing intimate partner violence (IPV). What people believe about the nature of IPV is likely to determine their propensity to intervene, but little is known at present about IPV beliefs among the general public. In a survey of 650 Swedish citizens, beliefs about the prevalence and causes of IPV, and viable means of intervention were assessed. Respondents estimated, on average, that IPV occurs in almost one quarter of all intimate relationships in Sweden, and that IPV is particularly prevalent in low-income groups, among non-European immigrants, in suburban areas, and in couples under the age of 50 years. Physical violence was believed to be the most frequent form of abuse in male offender-female victim cases, whereas psychological violence was considered most frequent in other combinations of offender and victim gender. Female respondents estimated a higher prevalence of IPV, attributed less blame to IPV victims, and suggested more means of intervention, than did male respondents. The findings are discussed in relation to empirical prevalence estimates, and implications are proposed.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.100
GPT teacher head0.409
Teacher spread0.309 · 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 designObservational
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

Citations17
Published2015
Admission routes1
Has abstractyes

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