Apprentice Life: Finding Life in the Way of Jesus
Bibliographic record
Abstract
The Apprentice Life: Finding Life in the Way of Jesus course is a project designed to address the difficulty of mobilizing more experienced believers at a large, western Canadian, evangelical anabaptist church to embrace their role in helping new believers grow up in their faith. The author has explored Old and New Testament teachings, various historic Christian traditions, contemporary faith formation theory, disciple-making literature, and the insights of local and expert contributors. Based on these discoveries, new believers are most likely to become resilient apprentices of Jesus when more experienced mentors in faith accept responsibility to pass on a living memory of God’s saving work through Christ and the Spirit through loving, intentional relationships. Apprentice Life provides a framework and content for a relational disciple-making and catechetical experience incorporating teaching, class and small group interaction, one-on-one mentoring, and personal exploration. Through a series of 13 interactive sessions, new believers (drawn from various evangelistic and seeker-oriented efforts) discover the key elements of basic discipleship; mentors receive training and resources for spiritual accompaniment, and journey alongside a new believer for the duration of the course.
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.
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 | 0.012 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".