Bibliographic record
Abstract
The attention to improve global health has developed significantly in the last decade through the introduction of dedicated scientific journals such as the International Journal of Evidence-Based Health Care, BMJ Quality and Safety and others. Furthermore, the ongoing involvement of major research funding bodies such as the National Health and Research Council, the Australian Research Council, the Canadian Institute of Health and Research and the National Health Institute in the United States and other organizations around the world have helped to fund important research projects to achieve equality in healthcare in their respective countries.1 Implementation of research findings across healthcare services will improve global health. This can be achieved through a scientific approach to understand how knowledge is translated into healthcare practice, management and policy to achieve the best health outcomes globally. As clinicians and researchers are engaged in providing and improving healthcare through different measures, many focus on targeting specific health profession groups, healthcare organizations or specialized clinical areas. A narrow targeted strategy may limit our progression in improving healthcare globally. The diversity of our disciplines in research, education and practice should enrich and strengthen our efforts to improve healthcare globally through engaging experts from a variety of disciplines, including behavioural economics, management science and systems engineering, to develop new models of care. We seek improved healthcare that effectively and equitably serve all people globally.2 Recognizing the culture differences between populations and achieving culture competency is also essential in reducing the health disparities experienced by many individuals worldwide. Evidence suggests that both health professionals’ leadership and diversity in institutional training are core areas to be targeted to improve healthcare globally. Leadership must be cohesive and supportive at executive levels and diffused throughout the various layers of the organizations. Diversity training must be embedded in programs across healthcare settings and should aim to raise awareness of the different health needs of patients.3 Creating international links between researchers and clinicians is essential in enhancing scientific discussion and creating a debate on how to establish a shared vision between stakeholders to provide scientific knowledge on how to improve healthcare globally.4 Other considerations for a successful research agenda to improve global health include: a defined target audience, identification of key research areas, context, understanding behavioural determinants, an implementation strategy and evaluation of change strategies, testing theories and other issues such as sustainability, knowledge infrastructure and workforce.5 The 9th Biennial 2014 Joanna Briggs Colloquium theme ‘Scaling new heights’ provides an international forum to discuss and challenge several beliefs around global health. The Colloquium focuses on improving healthcare globally through exploring some contemporary issues including; e-health as an innovative method for expanding evidence based practice and its impact on global health, revitalizing the fundamentals of care in the 21st Century, shared decision making and patients’ engagement in chronic disease management.
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 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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".