Biomechanical considerations on barefoot movement and barefoot shoe concepts
Bibliographic record
Abstract
The purpose of this paper is to discuss biomechanical considerations related to ‘barefoot running’ and ‘barefoot shoes’. Biomechanical differences include increases in external force loading rate, higher tibial acceleration, flatter foot placement, higher ankle joint stiffness and earlier EMG intensity for the tibialis anterior. There is indirect evidence that barefoot training strengthens small and large muscles crossing the ankle joint. Furthermore, there is evidence that barefoot running has energetic advantages over shod running. There is, however, no evidence that barefoot running would have more or less injuries than shod running. ‘Barefoot shoes’ include (a) the ‘Feet You Wear’ concept where the shape of the foot is mimicked, (b) the Nike Free concept where the kinematics of barefoot running are mimicked, and (c) the MBT (Masai Barefoot Technology) concept where the feeling of barefoot walking and/or running is mimicked. These shoes are based on very different conceptual ideas. However, all of them seem to provide a benefit to the athlete, independent on whether they are based on copying the shape of the human foot, the movement during barefoot running or the feeling of barefoot movement on soft ground. The name ‘barefoot shoes’ is a contradiction in terms. A shoe condition is not a barefoot condition. The discussed ‘barefoot shoes’ typically take one aspect of barefoot and implement it into a shoe. To assume that these shoes correspond to barefoot running or moving is not appropriate and the name ‘barefoot shoes’ may well be more a marketing strategy than a functional name.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".