Bibliographic record
Abstract
The of in Canada has come a long way in the past 50 years, with psychologists playing a critical role in not only advancing scientific understanding of the human condition, but also shaping practices and policies. The advance of psychological into practice and policy is highlighted by the report of the Canadian Psychological Association Task Force on Evidence-Based Practice of Psychological Treatments (2012). The task force recommends that psychological services not only be based on strong evidence, but also on continued and evaluation. Nevertheless, the challenges facing today are remarkably similar to those articulated by Adair (1981) 35 years ago. There are still inadequate funds for and grim employment prospects for emerging scholars, while at the same time, there is a pressing need for scientific understanding and approaches to address pressing social problems.I was one of 164 students who graduated with a PhD in in 1979, entering a field with declining academic growth and few academic positions (Adair, 1981). As a consequence, I was one of many psychologists who moved into applied positions and transformed formal training in into careers as full-time researchers, program evaluators, or practitioners (Adair, 1981). In this article, I highlight the journey and learning opportunities that I, along with many others, had when we stepped sideways into the applied world. There were multiple challenges and opportunities in collaborating with practitioners to re-create in real-world settings, which have been formative in my efforts to both contribute to psychology as a science and to public and community service.A Side Door to ScienceAs a newly minted postdoctoral fellow in 1984, I stepped into a clinical setting, Earlscourt Child and Family Centre (now Child Development Institute) as the Research Director. Within this clinical setting, there was a wish for research, but not a reality, so I started with small steps. My first assignment for successful research was counting the number of children who came into and out of service. As Bickman (2015) pointed out, these are the basic input and output metrics that clinical settings need for sustainability. The interest in and hope for research, however, came from many different program leaders within the Centre. The clinicians had burning questions about the characteristics of children and families coming into programs and about the outcomes of their programs. As a developmental psychologist, I was eager to learn about how children were developing through the programs and why. These early years of in a clinical setting taught me three important lessons. First, we had to spend a long period of time learning about each other's perspectives and articulating our questions of interest. It was a period of time in which I learned about the challenges that vulnerable children and their families face, as well as those of clinicians working to address these challenges. This extended time learning together formed the foundation for collaboration, which I discovered was absolutely essential for in a clinical setting. Second, it quickly became apparent that the only way that we could put programs under the microscope was by building trust in the process. It was essential to help clinicians understand that we were not examining them and their individual performances, but were interested in patterns in the treatment process. Finally, outside the controlled conditions of a labouratory requires extensive patience with the process, because it seldom unfolds in a timely and orderly fashion. Nevertheless, my colleagues and I slowly began to engage in cocreated research, some of which is still ongoing and thriving today, with significant contributions to the well-being of children and their families.New Questions and New PathwaysEarlscourt Child and Family Centre specialized in addressing the problems of aggressive children and their families. …
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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 | 0.078 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.025 | 0.042 |
| Scholarly communication | 0.025 | 0.017 |
| Open science | 0.006 | 0.021 |
| Research integrity | 0.013 | 0.023 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".