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Record W4411404710 · doi:10.47989/kpdc622

The need for deep rest: Six stories of critical grief pedagogy

2025· article· en· W4411404710 on OpenAlexaff
Kim Collins, Sarah Pierson, Janice Desroches, Guneet Bagga, Morgan Crosby

Bibliographic record

VenueJournal of Praxis in Higher Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsBrock UniversityUniversity of Toronto
Fundersnot available
KeywordsGriefNarrativeCognitive reframingTransformative learningPraxisPsychologySociologyPedagogyArtPsychotherapistPolitical scienceLiteratureLaw

Abstract

fetched live from OpenAlex

This paper reimagines the four tenants of critical grief pedagogy (CGP) through entwined narratives of and teachings on grief by introducing a fifth, essential tenant for engaging with CGP: the deep need for rest. Storied around their 2022 delivery of a digital Death Café for graduate students in a master’s-level disability justice course, Collins and Jones reframe CGP in the classroom through lenses of disability justice and methodologies of collective narrative. In collaboration with four student participants from the Death Café, this article responds to our interdependent grief experiences of the COVID-19 pandemic, climate change, madness, anticipatory grief, and the relationalities of these modes of grief. This paper is a gathering of those conversations and our collective writing. Through these narrative experiences, we engage in a mode of collaborative exploration, composition, and de-composition. We explore what it means to take teaching and learning as a ‘grief-facing’ praxis that changes how we engage with embodiment in higher education. In what follows, our entwined responses to the Death Café remind us that grief is ubiquitous and expansive in academic spaces, and that rest is essential and political.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.487
Teacher spread0.433 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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 routes1
Has abstractyes

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