Yin Yoga for Tense and Stiff Shoulder Pain 60 min | Yoga with Dr. Melissa West 422
Bibliographic record
Abstract
Are your shoulders are stiff and tense like mine? If you are like me I know you have tried a lot of things from massage, ibuprofen, heat and ice, and even exercises and movements to help relieve the shoulder pain. In this video I am going to show something different, how to get deep into the joint of the shoulder and prevent and reverse ligamentous contracture with yin yoga. Your shoulder is actually a ball and socket joint that has the potential for a large range of motion. The funny thing is that we actually do not move this joint alot. Most of the time our arms are in front of us typing on a keyboard or mobile device, making meals, lifting children, hugging our loved ones. Our arms don’t really move around a lot giving the shoulder a lot of range of motion. In Yin Yoga we stress our joints to prevent and reverse contracture or the loss of mobility through a joint. Yin Yoga can be helpful to slowly regain natural range of motion and relieve tense and stiff shoulder pain. The beautiful thing about yin yoga is that when we stay for awhile in the pose, for five minutes instead of the usual five breaths in a yoga class we are able to target the deeper connective tissues that wrap around the joints. Dr. Melissa West, from Victoria B.C. Canada has been releasing an hour long video every Friday on her YouTube channel since 2009. She specializes in helping you let go of all the tension, anxiety and stress in your life through yin yoga, restorative yoga, hatha yoga and yoga nidra/sleep yoga. If you are looking for a reprieve from the burdens of everyday life, Melissa’s videos offer the best in relaxation, peace and calm. Yin Yoga Sequence: Child’s Pose, Sphinx Pose, Melting Heart Pose, Reclined Twist, Savasana
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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) | 0.001 | 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) | 0.403 | 0.004 |
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".