Cognitive Processes Associated with the Perception of Randomness
Why this work is in the frame
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Bibliographic record
Abstract
In a study of novice teachers’ I investigate the conception of randomness among teachers college trainees thatstudy probability and statistics. I gave the students questionnaires which serve to explored their conception andproblem-solving approach with respect to probability problems, conception of randomness and deciding aboutthe randomness of sequences and arrays, solving a THOG type problem, which raise the use of matching biasescharacteristics. I will show that the students use a set of rules to solve these different categories of problems.There is a common heuristic for all or many of these problem solving categories: the problem solver relay onheuristics anchored on the symmetry and asymmetry of sets of objects or more abstract elements to decide onquestions like what is the probability of getting a certain sample in a random drawing of beads, the randomnessof an array; certain sequences are measured by looking at the amount of apparent order in-order to makedecisions concerning randomness and deviation from symmetry of the sample also effect the decision. Thischaracteristic heuristic approach of problem solvers is founded on a set of simple rules relating to order,deviation from symmetry, the distribution of patches in the plane and occurrence of ordered subsequences incertain linear arrangement of sequences.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it