Information critical for social work practitioners in the decision making process: An empirical study of implicit knowledge using naturalistic decision making perspective
Bibliographic record
Abstract
Knowledge derives from practice, or practice wisdom, is as important as formal knowledge in the clinical decision making process of social work practitioners.A number of theoretical studies of clinical decision making recognize the importance of this implicit way of knowing but there is a lack of empirical research that examines how implicit knowledge affects clinical decision making in social work treatment.The purpose of this study is to examine the existence of implicit knowledge from a cognitive science perspective and explore how it influences the clinical decision making process in social work practice.This study involves both deductive and inductive reasoning.Deductive reasoning derives a set of hypotheses from Naturalistic Decision Making (NDM) theory and uses experimental design to examine the relationships between implicit knowledge, experience and decision making.Inductive reasoning analyzes the participants' retention, diagnosis, reasoning, and clarification of the case scenarios as well as in-depth interview and utilizes content analysis to explore the nature of clinical decision making process by comparing the differences between experienced and inexperienced practitioners.The validity of the study was established through face validity and content validity as well as the application of various experimental designs.The reliability of the study was established through inter-coder correlation (with r =.96 in Scenario A and with r = .98 in Scenario B) in retention coding and inter-coder agreement (with Kappa = .95) in interview coding.The iii verification of the study was established through triangulation, member check, and peer examination.The suitability of the experiment instrument was established through fox index (with FI = 5.6 in Scenario A and FI = 4.4 in Scenario B).Findings from deductive reasoning support the usage of implicit knowledge but do not support the assumption that experienced participants have a better understanding of the client's situation than inexperienced practitioners.Findings from inductive reasoning conclude that making diagnosis is a continuing and ongoing process of understanding clients' situation.Findings pertaining to the structure of information retained by research viii
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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 | 0.045 | 0.211 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".