Speaking Up for Fundamental Care: the ILC Aalborg Statement
Bibliographic record
Abstract
OBJECTIVE: The International Learning Collaborative (ILC) is an organisation dedicated to understanding why fundamental care, the care required by all patients regardless of clinical condition, fails to be provided in healthcare systems globally. At its 11th annual meeting in 2019, nursing leaders from 11 countries, together with patient representatives, confirmed that patients' fundamental care needs are still being ignored and nurses are still afraid to 'speak up' when these care failures occur. While the ILC's efforts over the past decade have led to increased recognition of the importance of fundamental care, it is not enough. To generate practical, sustainable solutions, we need to substantially rethink fundamental care and its contribution to patient outcomes and experiences, staff well-being, safety and quality, and the economic viability of healthcare systems. KEY ARGUMENTS: We present five propositions for radically transforming fundamental care delivery:Value: fundamental care must be foundational to all caring activities, systems and institutionsTalk: fundamental care must be explicitly articulated in all caring activities, systems and institutions.Do: fundamental care must be explicitly actioned and evaluated in all caring activities, systems and institutions.Own: fundamental care must be owned by each individual who delivers care, works in a system that is responsible for care or works in an institution whose mission is to deliver care. RESEARCH: fundamental care must undergo systematic and high-quality investigations to generate the evidence needed to inform care practices and shape health systems and education curricula. CONCLUSION: For radical transformation within health systems globally, we must move beyond nursing and ensure all members of the healthcare team-educators, students, consumers, clinicians, leaders, researchers, policy-makers and politicians-value, talk, do, own and research fundamental care. It is only through coordinated, collaborative effort that we will, and must, achieve real change.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".