Psychology in Canada (University of Alberta Press).
Bibliographic record
Abstract
There can be few, if any, psychologists who are unaware of the Tarasoff v. Regents of the University of California (1976) decision and the impact it has had on the profession of psychology. Psychologists are often privy to the most intimate aspects of clients' lives. But this knowledge can be a double-edged sword when concern arises that a client may pose a threat to others. A ethical conflict arises between the psychologist’s professional obligation to respect the autonomy of the client, and an obligation to protect the foreseeable victims of the client’s violent actions. Legal practitioners frequently speak in terms of legal duties owed between people. In stating that a legal duty exists they are saying, in shorthand, that in light of all policy considerations a particular standard of conduct is owed by one person to another. In the absence of such a duty there is no obligation to act in a particular manner. Such duties may be created by the legislature, by the courts, or by the general understandings of everyday existence. What is important to understand is that to state that a legal duty exists is to draw a conclusion based on the facts of a certain situation, and not a statement of fact in itself.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.233 | 0.056 |
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".