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Record W4393870929 · doi:10.32920/jcd.v7i1.1860

Pain and Progress

2024· article· en· W4393870929 on OpenAlexfundvenueno aff
Eric Ng, Mikahelia Wellington, Nadia Pabani

Bibliographic record

VenueJournal of Critical Dietetics · 2024
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMedicinePsychology

Abstract

fetched live from OpenAlex

BackgroundRecent intersecting crises such as the protests against anti-Black racism after the public murder of George Floyd and the call for reconciliation with Indigenous peoples following the discovery of thousands of unmarked graves of children at multiple former Residential Schools, have drawn mainstream attention, to issues related to colonization and racism, against which advocates have long spoken.The COVID-19 pandemic has also revealed the persistent social inequities experienced by Indigenous, Black, and racialized communities in Canada as they are Volume 7, Issue 1 ISSN 1923-1237 over-represented by COVID-19 cases and barriers to accessing health services (Toronto Public Health, 2022).While racism and colonization have been well-documented in Canada, the recent public awareness of these issues, once considered "fringe," has pressured organizations to name and address these forms of oppression.In Canada, anti-oppressive practice literature emerged from the critical social work scholarship in the early 2000s.Scholars and advocates pointed to the unjust social structures and policies in which social work is embedded and called on practitioners to challenge these oppressive systems in their practice (Mullay, 2002& Baines, 2007).This however, has not been the priority for dietetics, which has been behind in its recognition for this work despite the efforts of BIPOC (Black, Indigenous, People of Colour) dietitians and allies calling for the need for anti-oppressive education (for example, Djulus et al., 2022) within the education institutions (Wellington et al.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.062
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0620.018

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 head0.019
GPT teacher head0.340
Teacher spread0.321 · 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 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".

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Citations0
Published2024
Admission routes2
Has abstractno

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