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Record W7037873487

Exploring violence against socially vulnerable Inuit women in Denmark

2023· other· en· W7037873487 on OpenAlexaboutno aff

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2023
Typeother
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchEthnic groupPerspective (graphical)PopulationGovernment (linguistics)Agency (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

This paper aims to explore violence against socially vulnerable Inuit women in Denmark.This paper will study why socially vulnerable Inuit women are exposed to violence, what type of violence they are victims of and whom the perpetrators are in Denmark.The data used in this study consists of semi-structured interviews with professionals, who work or have worked with socially vulnerable Inuit women in Denmark.A methodological approach by Braun and Clarke, the thematic analysis is applied.The results showed the colonization of Greenland created historical trauma which has led to intergenerational trauma and consequently influenced mental health, substance abuse and violence.Additionally, a normalization of violence is present in Greenland and in the socially vulnerable environment in Denmark.Furthermore, a lack of knowledge about Inuit in the Danish system influence Inuit women to social exclusion in Denmark.These women are subjected to all types of violence by someone they know, either friends, family, friends of the family, current or previous partners.These results will be discussed with in the theoretical framework of intergenerational trauma and normalization process theory.Therefore, socially vulnerable Inuit women in Denmark are victims of intimate partner violence and are subjected to physical-, sexual-, psychological-, and economical violence, influenced by intergenerational trauma and a normalization of violence.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.045
GPT teacher head0.273
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueKTH Publication Database DiVA (KTH Royal Institute of Technology)Same topicSilk-based biomaterials and applicationsFrench-language works237,207