Bibliographic record
Abstract
Purpose in nursing, Nursing education, Equity and anti-racism, Professional identity few weeks ago, my colleague told me about this invitation to write about the concept of purpose in healthcare.I ignored it at first -too many tasks, too little time.But even as I moved on with my days, the question lingered quietly in the back of my mind.What would I write if I let myself pause long enough to answer?I didn't open a blank document right away.Still, the story began anyway, unfolding softly.And today, I find myself ready to start.I'm inviting you into that story -the one that's been forming, slowly and unexpectedly, since the moment I chose not to respond.I am a nurse and currently a Faculty Lecturer at a school of nursing.Reflecting on my professional life, Irealize that a consistent pursuit of purpose has shaped it.Whether at the bedside, in the community, or classrooms, my actions are guided by a clear sense (or need) for meaning and contribution.My most recent full-time clinical role was at a community health center.I was doing home visits for families welcoming a baby into their lives.Despite the struggles and hardships of life, it was generally a setting filled with great joy.It was in that role -entering people's homes, holding space for their stories, and walking alongside them through significant life transitions -that my understanding of purpose deepened.These experiences weren't just clinical duties; they were human moments that reaffirmed why I chose this profession in the first place.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.051 | 0.066 |
| Scholarly communication | 0.019 | 0.026 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.013 | 0.038 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".