Bibliographic record
Abstract
In 1978, Barbara Carper named personal knowing as a fundamental way of knowing in our discipline. By that, she meant the discovery of self-and-other, arrived at through reflection, synthesis of perceptions and connecting with what is known. Along with empirics, aesthetics and ethics, personal knowing was understood as an essential attribute of nursing knowledge evolution, setting the context for the nurse to become receptively attentive to and engaged within the interpersonal processes of practice. Although much has been done over the 40 years since Carper described these ways of knowing, and we have seen enormous advances in empirics and ethics, and I would argue even in aesthetics (understanding the subtle craft of nursing in action), personal knowing may not have attracted its fair share of critical unpacking. Further, we see increasing evidence of a distortion on how forms of personal knowledge, including beliefs and attitudes, are being taken up within segments of the profession; these include legitimizing idiosyncratic positionings and, most worrisome, challenges to the idea that there are and ought to be fundamental truths within nursing that stand as central to disciplinary knowledge. In this paper, the author reflects on the confusion that a continued uncritical deference to personal knowing may be creating and the evolving interests it seems to serve.
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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 | 0.030 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.018 | 0.127 |
| Scholarly communication | 0.023 | 0.027 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.013 | 0.025 |
| 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".