Developing positive self-leadership through “Inner Engineering”
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The study evaluated the effect of a comprehensive yogic methodology called “Inner Engineering Online” (IEO) on developing positive self-leadership. The authors hypothesized that IEO would equip participants with knowledge and skills to optimize their functioning in major experiential dimensions of the self (body, mind, emotion, and energy) and produce a synergistic effect in enhancing well-being and positive organizational behavior for employees, leaders, and entrepreneurs. Design/methodology/approach The study uses a field quasi-experimental one group design with pre- and post-tests. The sample consists of 97 employees, 84 leaders and 76 entrepreneurs in various industries ( N = 264). Findings The pairwise t -test results show that IEO has a positive effect on well-being (mindfulness, joy, vitality, and restfulness) and positive organizational behavior (meaningful work, psychological capital, and work engagement). Research limitations/implications The study is limited by the lack of a control group. Future research may use a randomized control design to confirm the present findings and explore the mechanisms through which IEO exercises its effect and other positive outcomes. Practical implications IEO complements the behavioral and cognitive strategies of self-leadership by including emotional and energetic strategies to produce a synergistic effect on positive outcomes. The program is multi-lingual and scalable and can be implemented in and outside of the organizational settings globally. Originality/value The study proposes the concept of positive self-leadership and is the first study to investigate the potentiality of an emerging program for developing positive self-leadership.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.008 | 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