Memahami Kristologi Menurut Kolose 1:28 Untuk Membina Jemaat Melalui Model Partners in Learning
Bibliographic record
Abstract
The purpose of this journal is to apply the principles of fostering church members through the teaching model of partners in learning where coaches and congregations emphasize the importance of relationships to build trust between the two parties. As was done by the Lord Jesus Himself in His ministry, namely building relationships with the people He served, this partner in learning model also applies the importance of acceptance and appreciation between personal mentors and the congregation. Some of the impacts of the partners in Learning model: (1) Involvement means increasing the partnership between tutors and students, (2) Awareness. This model helps mentors and students to develop metacognitive awareness and a growing identity, (3) Improvement. Learners are more active and responsible for the learning program that is being carried out. Partners in learning change the way of 'telling students about topics they need to know' to facilitating them to get the necessary information (inquiry). Partners in learning will produce students like Paul taught in Col. 1:28 namely growing towards maturity towards Christ.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".