Nurses and Lifelong Learning: Creating “Makers and Shapers” or “Users and Choosers”?
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.
Bibliographic record
Abstract
PROBLEM: How have the meaning and goals of lifelong learning for nurses shifted under neoliberal political policy? METHODS: This article critically scrutinizes the political undercurrents of lifelong learning. While the original intent of lifelong learning was to foster intellectual, critical, social, and political citizen engagement (creating "makers and shapers" of social policy), instrumental learning-learning to meet practical economic ends-has taken priority and is instead creating marketable workers (creating "users and choosers"). FINDINGS: International educational neoliberal policy reform has altered the very nature of education. Under pervasive neoliberal political influence, lifelong learning has become distorted as the goals of learning have shifted towards creating marketable workers who are expected, while unsupported, to engage in learning to ensure ongoing employability in an open market. CONCLUSIONS: By examining new understandings of lifelong learning, nurses can make informed choices as to whether they aspire to be a "user and chooser" or "maker and shaper" of lifelong learning in their workplaces.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it