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Record W3149790558 · doi:10.1111/jan.12124

Comment on: Thompson D.R. &amp; Darbyshire P. (2013) Is academic nursing being sabotaged by its own killer elite? <i>Journal of Advanced Nursing</i> 69 (1), 1–3.

2013· letter· en· W3149790558 on OpenAlexaboutno aff
Wendy Cross, Allison Williams

Bibliographic record

VenueJournal of Advanced Nursing · 2013
Typeletter
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipExcellenceBachelorNurse educationSociologyNursing researchEliteNursingMedical educationMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

on.There, as a compensation for the near absence of a conventional academic background and little [if any] previous personal experience of conducting real-life nursing research (White 2012), their light-weight contributions to business can be overzealous, pedantic and arduous.Self-serving publicity can reach legendary proportions, especially when privileged access to print and other media outlets is available.This can reap an additional dividend of appearing to outstrip the publication track records of otherwise stronger colleagues.When these publications are boiled-up, however, much can be evaporated-off as mere rhetoric.Some years ago, it was commonplace to hear the adage 'if you can't do the scholarship, be controversial'.For those who lack the gravitas, this has remained a mantra.The occasional attraction of modest insider research grants to conduct self-indulgent small-scale inconsequential studies, or presentations at local workshops amongst groomed sycophants, only fashion the mirage of productivity.The sobering upshot of these sleights of hand by those who have accepted appointments to box above their weight, and others who are complicit in maintaining them, is that they are most unlikely to ever work in the service of the nursing profession per se nor, by extension, the best interests of patient care.Both deserve better.Therefore, the Editorial by Thompson and Darbyshire (2013) should be read widely.Doubtless, it will attract some howls of indignation from predictable quarters.However, wiser academics may be relieved to read a public account that resonates loudly with their own experience and will be encouraged to strengthen their personal and collective resolve to bring about positive change and increase high-quality research capability and capacity in contemporary professional 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.

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)0.006
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.996
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0040.004
Scholarly communication0.0050.007
Open science0.0060.003
Research integrity0.0380.040
Insufficient payload (model declined to judge)0.0150.017

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 head0.020
GPT teacher head0.329
Teacher spread0.309 · 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.

Study designNot applicable
DomainIncentives
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

Citations1
Published2013
Admission routes1
Has abstractyes

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