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Record W2995560186 · doi:10.25071/2291-5796.27

A Right to Vote: A Case Study in Nursing Advocacy for Public Policy Reform

2019· article· en· W2995560186 on OpenAlex
Abe Oudshoorn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWitness The Canadian Journal of Critical Nursing Discourse · 2019
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsWestern University
Fundersnot available
KeywordsPublic administrationLegislationVotingPolitical sciencePolicy advocacyGovernment (linguistics)Public policySocial justiceEconomic JusticeWelfare reformPatient advocacyPublic relationsLawSociologyLaw and economicsPoliticsWelfareMEDLINE

Abstract

fetched live from OpenAlex

In February 2014, the Government of Canada under Stephen Harper introduced the ‘Fair Elections Act’. This reform to the elections act removed provisions for access to voting for individuals lacking certain forms of identification. Noting that this would have a disproportionate impact on people experiencing homelessness, nursing advocates joined with other activists to try to prevent then subsequently overturn this legislation. The purpose of this paper is to explore the 93rd competency of the College of Nurses of Ontario, “Advocates and promotes healthy public policy and social justice,” by unpacking a case example of advocacy for voting rights. This paper addresses the challenges faced by nurses in doing public policy advocacy and concludes with lessons learned. Fulfilling our college mandated requirement to be politically active means ensuring that public policies are just, equitable, and reflective of the progressive values of Nursing.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.396
Teacher spread0.361 · 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