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Record W3017970382 · doi:10.7202/1068547ar

TOWARDS A RECOGNITION OF THE PLURALITY OF KNOWLEDGE IN SOCIAL WORK

2020· article· en· W3017970382 on OpenAlexvenueno aff
Lisa Ellington

Bibliographic record

VenueCanadian social work review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsVisionIndigenousIdeologyContemplationSociologyContext (archaeology)Presentation (obstetrics)PoliticsSocial workWork (physics)Social scienceEnvironmental ethicsSocial changeEpistemologyPublic relationsPolitical scienceMedicineLawAnthropologyGeography

Abstract

fetched live from OpenAlex

Social work as a profession has undergone significant change in recent decades, modulated by the various social, political, and organizational transformations of the society in which it evolves. Today, there is increasingly diversified research encompassing a number of coexisting visions of social work. These multiple visions come hand in hand with values, principles, as well as ideologies, some of which are dominant, and others that are marginal. Indigenous Peoples are among the most marginalized groups in society and so are Indigenous worldviews within the profession. Currently, there seems to be a willingness to recognize the plurality of knowledge in the area of social work. In line with this objective, the purpose of this article is to present the Indigenous research paradigm. This is a theoretical contemplation centered around the historical context that led to the paradigm’s creation, a description of what it consists of, as well as a presentation of a few examples of its use by social work researchers. Finally, the paper brings up certain persistent issues related to the recognition of the Indigenous paradigm within the profession.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.339
Teacher spread0.269 · 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 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

Citations10
Published2020
Admission routes1
Has abstractyes

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