Commencing Self Directed Learning to Heutagogy Skill in Lieu of Spiritual Entrepreneurship
Bibliographic record
Abstract
The problems faced by the retirement age group are increasingly complex. Declining productivity, income and welfare. The transition period from the productive workforce to the gray entrepreneurship has not been followed by an optimal learning process. The research objective is to obtain an overview and analyze the entrepreneurial orientation of retirees who have the ability to learn independently. The explanatory survey method on the entrepreneurship training participants in the preretirement program at an educational and training institution is at PT Meta Bright Vision (MBV) in Bekasi. Questionnaires were distributed to 155 respondents. Path analysis was used to analyze the data. The research then revealed that respondents who successfully applied Self Directed Learning had the ability to create value as basic skills to face a productive period of retirement. The ability to identify the knowledge, skills and processes needed for meaningful learning about entrepreneurship leads to an understanding of value creation. Independent learning to understand the learning process determines how entrepreneurial behavior in the retirement age group. Encouraging heutagogy skills in the retirement age group is a need to remain productive in the golden age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".