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Record W4405435995 · doi:10.25071/2291-5796.169

Rethinking Children’s Nursing: Critical learnings from Childhood Studies

2024· article· en· W4405435995 on OpenAlexaffvenue
Franco A. Carnevale

Bibliographic record

VenueWitness The Canadian Journal of Critical Nursing Discourse · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsMcGill University
Fundersnot available
KeywordsOppressionCONTESTSociologyParticipatory action researchMaturity (psychological)Gender studiesCitizen journalismPsychologyPolitical scienceDevelopmental psychologyPoliticsLaw

Abstract

fetched live from OpenAlex

Within this commentary, I contest dominant views and practices regarding im/maturity within Children’s Nursing that are rooted in refuted age-based conceptions of child development. I highlight how these operate as forms of epistemological oppression that perpetuate the exclusion of young people’s voices and experiences in research, policymaking and practice development that affects them. These dominant approaches breach their participation rights and can generate significant distress and trauma. To counter these oppressive views and practices, I discuss an inclusive participatory framework that is centered on the recognition of young people as human agents, acknowledging their voices as forms of agential expression and action. I argue that all research, policymaking and practice development that affects young people should be informed by their aspirations and concerns expressed through respectful – not tokenistic - youth engagement initiatives. I argue for an urgently-needed restructuring of Children’s Nursing theory and practice.

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)0.055
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.292

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.068
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0300.116
Scholarly communication0.0280.022
Open science0.0070.019
Research integrity0.0150.029
Insufficient payload (model declined to judge)0.0030.000

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 head0.410
Teacher spread0.357 · 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 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
Published2024
Admission routes2
Has abstractyes

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