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Record W1964645292 · doi:10.1080/15426432.2011.587387

Challenging Anthropocentricism in Social Work Through Ethics and Spirituality: Lessons from Studies in Human-Animal Bonds

2011· article· en· W1964645292 on OpenAlexaffabout
Cassandra Hanrahan

Bibliographic record

VenueJournal of Religion & Spirituality in Social Work Social Thought · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAnthropocentrismSpiritualitySociologySocial workEnvironmental ethicsField (mathematics)Value (mathematics)Diversity (politics)Engineering ethicsEpistemologyPerspective (graphical)Political scienceLawMedicine

Abstract

fetched live from OpenAlex

During the process of teaching theoretical foundations in a Canadian school of social work, I sought to combine my teaching of critical anti-oppressive practice (AOP) with established ideas from the field of human-animal bonds (HAB) and from the spiritual experiences arising within my relationships to companion animals. This article addresses the challenges I confronted by identifying speciesism, a specific form of discrimination based on species not recognized within social work's anti-oppressive practice paradigm. I argue that anti-oppressive social work is, in effect, oppressive because it informs a perspective that prioritizes humans over other animals, nature, and the planet. By drawing on the extensive body of literature in the field of HAB, which like AOP is informed by critical social theories, this article highlights how an AOP approach is delimited to diversity among humans. The implication of anthropocentrism as the central organizing principle of AOP social work is that it limits the profession's value framework and the potential for sustainable outcomes for well-being among all beings. Pathways to address these implications are offered by reference to work that explores issues of spirituality and ethics in both social work and HAB research.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.006
Science and technology studies0.0060.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.004
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 head0.294
GPT teacher head0.493
Teacher spread0.198 · 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 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

Citations45
Published2011
Admission routes2
Has abstractyes

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