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Record W7072129620

Utilizing feminist theories when working with older adults in acute care: social workers' perspectives

2018· article· en· W7072129620 on OpenAlexfundno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
FundersUniversity of the Fraser Valley
KeywordsFeminist theoryPower (physics)Social theoryPsychological resilienceGrounded theoryOrder (exchange)Social workFeminism
DOInot available

Abstract

fetched live from OpenAlex

Social workers frequently engage with older adult patients when working in an acute care\nhospital setting. In order to be effective in their work, each social worker must be informed by\nand utilize one or more theoretical frameworks in their practice with each patient. One of the\ntheoretical frameworks that can be used when working with older adult patients is feminist social\nwork theory. Utilizing both a feminist and a post-modernist lens, this study looks at how feminist\nsocial work theory is applied when working with older adult patients in acute care. In order to do\nso, five acute care social workers who utilized feminist theory in their practice were interviewed\nin order to gain their perspectives on when they apply feminist theory and how they find it\nbeneficial for their patients. Themes that were developed from the interviews include:\nquestioning society-created presumptions due to one’s gender and age, understanding the\nnegative effect of the power imbalances between the patient and other involved parties, and\nencouraging both patient and social worker resilience to oppression. The themes that emerged\nfrom the interviews demonstrate how these social workers believe feminist theory is best utilized\nin their practice and when it has been found to be most effective.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0500.000

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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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.

Study designTheoretical or conceptual
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
Published2018
Admission routes1
Has abstractyes

Explore more

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