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Record W4414436428 · doi:10.1093/bjsw/bcaf194

‘We’re handing out freezies’: Climate-related professional challenge and changing social work practices in the homelessness sector

2025· article· en· W4414436428 on OpenAlexafffundabout
Mélissa Roy, Emmanuelle Larocque, Nikolas Parent-Poisson, Sue-Ann MacDonald, Sean A. Kidd

Bibliographic record

VenueThe British Journal of Social Work · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of TorontoUniversité de MontréalUniversité du Québec en OutaouaisCentre for Addiction and Mental HealthUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council
KeywordsWork (physics)Transformative learningThematic analysisSocial workFace (sociological concept)Identity (music)Adaptation (eye)

Abstract

fetched live from OpenAlex

Abstract Climate change’s disproportionate impact on people experiencing homelessness has a collateral effect on community-based organizations. Relying on the concept of ‘professional challenge’, this research is interested in: (1) the ways that social work professionals are challenged by new climate realities; (2) the tensions they navigate when their actual work differs from anticipated and prescribed work; and (3) the strategies they put in place to alleviate these tensions. We facilitated three focus groups with seventeen social work professionals from various community-based organizations working in homelessness in Quebec (Canada). A thematic and argumentative analysis shows that professionals rely on three strategies to overcome the ‘climate challenge’: the quantitative increase in services, the adaptation of practices, and the confrontation of obstacles. They illustrate how new climate realities widen the gap between anticipated/prescribed work and actual work and show that in the face of emergencies, actual work is conducted within a logic of adaptation, rather than in a transformative paradigm. Additionally, results show that the gap between anticipated/prescribed work and actual work generates teleological, ethical, and professional identity tension. To alleviate these tensions, professionals engage in emotional and discursive labor by constantly (re)negotiating guiding axiological, humanitarian, and ethical principles. Implications for practice are discussed.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0110.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.066
GPT teacher head0.404
Teacher spread0.337 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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