Bibliographic record
Abstract
Introduction 1.1 OverviewThe general public learns about mental illnesses and addictions primarily from mainstream media, including news reports, television programs, and movies.The stories presented usually centre on sensationalism or danger such as those about young women at lifethreatening stages of anorexia nervosa or people labelled as "psychopaths."Or the stories appeal to our feelings of sympathy or empathy such as those about people with untreated mental illnesses sleeping on subway vents during winter or a person with moderate dementia who finds greater companionship with someone other than their spouse.These reports and programs often oversimplify the ethical nature of these situations by dramatically pitting one value against another: self-determination versus life, public safety versus rehabilitation, quality of life versus non-abandonment, and happiness versus loyalty.Distilling situations down to one or two values can be motivated more by the ongoing competition for the public's attention and/or economics than by the demands of concise reporting.However, mental illnesses and addictions are complex, as those who live with a mental health or addiction problem and their families can attest.The high incidence of mental health and addiction problems and their disruptive and lasting impact on people's lives, families' sustainability, communities' well-being, and employers' productivity are publicly acknowledged more often now.In recent years, more and more governments (civic, provincial/state, national) and employers have become interested in listening to those with first-hand experience of these conditions and to those who have developed holistic, integrative ways to diagnose and offer treatments and supports earlier and longer.Ethical complexity is not limited to crises and strong emotions.It exists in everyday, seemingly routine questions, experiences, and situations.The cases in section 1.2, below, help illustrate the wide diversity of ethically complex, "real world" situations that those living with a mental health or addiction problem, their families and friends, professional healthcare workers and their managers commonly face.Accordingly, the selected cases involve a variety of participants, interests, contexts, histories, health problems, options, and values.The healthcare ethics literature---which is quite extensive now---and educational workshops and courses encourage their readers and participants to increase their understanding of a particular situation or question and they offer various theories, concepts, www.intechopen.com
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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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".