Mentoring Approaches Preferred by Mentors in Their Work With Immigrant Youths
Bibliographic record
Abstract
The aim of the present study was to examine the preferred approach used by mentors to work with immigrant youths, describe how they carry out their work and why they chose to work that way, and analyze what is their initial assumption in their work with immigrant youths. The approaches are personal growth, mentoring as situational learning, mentoring that focuses on problem-solving problem and mentoring as a research process. One hundred and fifty mentors participated in the study. Each of them worked regularly with five Israeli immigrant youths. The findings show that the mentors adapted the work process to their mentees, but chose an approach that best suited their personality and worldview. A mentor who preferred the “mentoring as personal growth” approach may find it difficult to work in the “mentoring as situational learning” approach. All mentors mentioned a sense of mission they had in working with immigrant youths. The mentors used concepts such as “awareness” and “mindfulness,” and spoke about the attention that allows the mentor and mentee a focused view of the present, of what is happening here and now, as a key to a meaningful process in each of the approaches. All the mentors mentioned the principle of communication as a central principle in their work and the importance of having a meaningful dialogue with the mentees. Another principle mentioned by all the mentors was that of building trust between them and their mentees. They developed the mentees' confidence in themselves and their abilities, in the sense that they were capable enough to act, perform, and succeed; and developed trust in the fact that the mentors did want what was best for the mentees, accepting the mentees with their strengths, impulses, and weaknesses.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".