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Record W4321513651 · doi:10.7202/1096801ar

IN THE WAKE OF COVID-19: REFLECTING ON SOCIAL WORK’S CLIMATIC FUTURE

2023· article· en· W4321513651 on OpenAlexvenueaboutno aff
Timothy B. Leduc

Bibliographic record

VenueCanadian social work review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsAnthropoceneEnvironmental ethicsSociologyPoliticsClimate changePolitical sciencePolitical economyLaw

Abstract

fetched live from OpenAlex

We have moved into an era some call the Anthropocene, a time when nothing is untouched by the seeming unending expansion of modern systems (political, economic, cultural, virtual) and their inevitable global impacts. In many ways, COVID-19 intensified our awareness of this global interconnectivity not only through contact-tracing the pandemic, but also through its varied impacts on modern systems that further highlighted our ongoing dance with global and local environmental changes. The interconnected nature of our climate of change is revealing to us the partial, dualistic and ultimately limited modern worldview that continues to constrict the social justice principles our vocation of social work holds as its ideal. Something is out of balance and we need to work upon this imbalance in ways that do not deny the loss, confusion, injustices and power-grabs highlighted in the wake of COVID-19. Through approaching our climate of change in this way, we are given an opportunity to reflect on social distancing in relation to honouring boundaries, the value of slowing down modern ways of living, and the need to look more closely at our modern blocks to a sustainable future on planet Earth; in other words our climatic truth-work. In this article, I reflect on what Canadian society, the social work profession and the international community have learned (or not learned) from the pandemic about the climate of cultural change before us.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.619
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.012
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.195
GPT teacher head0.483
Teacher spread0.288 · 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
GenreCommentary

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 routes2
Has abstractyes

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