Bibliographic record
Abstract
The Invisible Influences on Decision-Making explores the often unseen factors that influence decision-making in both everyday life and various professional settings, with a particular focus on policing, medicine, education, and counselling. Chitpin and Dougan present key findings and trends in decision-making research, then go on to explore the concept of indecisiveness before examining decision-making processes in these specific professions. The authors employ qualitative research methodologies, such as case studies and phenomenology, alongside social influence theories, to provide a nuanced and current understanding of decision-making within these fields. By incorporating perspectives from professionals, chapters aim to enhance public understanding and confidence in how decisions are made in these critical areas, especially within a Canadian context. While there is existing literature on decision-making in community service professions, it often remains discipline specific. The Invisible Influences on Decision-Making addresses the need for more inter-professional and interdisciplinary research, highlighting the collaborative nature of these professions and the complexities of their decision-making processes. By integrating real professional examples with research and theory, this study offers a compelling and insightful narrative that will engage researchers, practitioners, and graduate students across various fields.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".