Bibliographic record
Abstract
PRISM is a visual instrument that improves a person's cognitive reasoning by facilitating the process of thinking. Its origins stem from efforts and experiences of psychotherapeutics in the early 1990s. Meanwhile the PRISM methodology - an acronym for «Pictorial Representation of Selfness III-Measure» - has spread wider to such domains as coaching processes, participant feedback and project management. This paper outlines a pattern language that should help PRISM facilitators to realize specific PRISM features when adapting this instrument to their dedicated domains. Research has shown strong effectivity and efficacy of using PRISM. Its modus operandi is based on a number of theoretical concepts like the relationship between humans and tools, the presentation of thoughts in a brain as mental models, and the power of visual metaphors. The author aims to extract and outline some patterns that seem to be key drivers to achieve most benefit from PRISM and will hopefully lower the threshold for those who want successfully leverage this methodology for their own purposes.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".