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Record W7037208320

Dimensions of Critical Social Work Practice in India

2023· article· en· W7037208320 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldComputer Science
TopicMetaheuristic Optimization Algorithms Research
Canadian institutionsMacEwan University
Fundersnot available
KeywordsSocial changeOppressionSocial philosophySocial workSocial positionSocial orderEmancipationSocial relationSocial inequality
DOInot available

Abstract

fetched live from OpenAlex

Critical social work opens a dialogue for social change by challenging the prevailing socio-economic conditions of the people and examining the underlying factors that contribute to the inequality and misery of people. Critical social work includes different theoretical and practice frameworks such as radical social work, anti-oppressive social work, and environmental social work. As a practice approach, critical social work applies to working with individuals, groups, and communities as well as in the clinical and developmental sectors. While all the approaches have their scope of practice in India, this article will focus on understanding and applying structural social work, feminist approaches to social work and Dalit social work in the Indian context. Considering the country's social context, it can be argued that Dalit social work falls within critical social work in India, where the writings and actions of Dr. B.R. Ambedkar contribute to critical social work in India and other parts of the world. The article critically analyses power structures in the country and the manifestation of oppression in different forms and discusses how the practice of critical social work can aid in personal liberation and emancipation in an Indian context.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.006
Science and technology studies0.0290.070
Scholarly communication0.0220.006
Open science0.0030.023
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.294
GPT teacher head0.604
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2023
Admission routes1
Has abstractyes

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