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Record W3182645550 · doi:10.1093/bjsw/bcab064

Indigenization without ‘Indigeneity’: Problematizing the Discourse of Indigenization of Social Work in China

2021· article· en· W3182645550 on OpenAlexaff
Tsering Dolkar Watermeyer, Miu Chung Yan

Bibliographic record

VenueThe British Journal of Social Work · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenizationIndigenousSociologyGender studiesPraxisChinaPolitical scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Abstract While acknowledging mutual alignment in their critique of social work’s dominant Eurocentric lens, indigenous and indigenization of social work have thus far forged separate routes. Indigenous social work predominantly focuses on groups in the settler colonial states of North America and Australia where the term ‘indigenous’ as an official identity category is embraced by groups to signify their a priori territorial claims, traditional way of life, and distinct world views. Indigenization of social work, on the other hand, primarily deals with the effective transmission of praxis in non-western regions. Yet complex linkages between the two exist that impacts the trajectory of indigenization of social work. This article draws upon indigenous theorizing and transdisciplinary learning to examine the neglect of highly charged concepts such as ‘indigenous’ and relationally notions of indigeneity within the social work indigenization discourse in China. Further, grounding the analysis within the liminal sphere of China’s ethnic minorities, particularly the case of Tibet Autonomous Region, it presents a preliminary discussion on potential ways to conceptualize ways forward.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.331
Teacher spread0.312 · 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 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

Citations3
Published2021
Admission routes1
Has abstractyes

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