Mechanisms of Compensation of the Driver's Sense of Dimensions
Bibliographic record
Abstract
The research paper analyzes the peculiarities of training candidates for drivers for certain subtypes (components) of combined driving. The work is focused on the analysis of opportunities to improve the quality of training of drivers for such subtypes of driving as orientation on the road, which, in particular, is the basis for mastering parking manoeuvres. Based on the analysis of a number of works, less confidence of women in driving a vehicle in a limited space (as opposed to men) is shown, which is manifested in the choice of simpler tasks for this subtype of activity. The psychological nature of the sense of dimensions is analyzed, the importance of visual sensations and long-term memory for the formation and development of this feeling is shown. The hypothesis about the possibility of compensating for the insufficiently developed and worsening with age sense of dimensions due to reliance on visual figurative memory and subject reflection is formulated. The results of the empirical study, which found the relative independence of the level of development of linear and angular eye estimation and confidence in parking with different driving experience, are presented. The results of the analysis of the tasks for reflection of driving in a limited unstructured space by 100 drivers are presented, which confirm the hypothesis of the study: visual landmarks for parking in non-standard conditions, in percentage terms, are more often identified by older drivers with longer experience but with poorer indicators of linear and angular eye estimation, being no different in terms of parking confidence from young drivers with better eye estimation, which can be considered as a manifestation of the compensation mechanism.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".