Act, Talk, Reflect, Then Act: The Role of Natural Mentors in The Critical Consciousness of Ethnically/Racially Diverse College Students
Bibliographic record
Abstract
The current mixed-method study examined the role of natural mentors in the cyclical process of college students' sociopolitical development, particularly their critical consciousness. College students (N = 145) completed surveys at two time points over a one-year period. Path analyses indicated that critical action and perceived inequalities were significantly associated with more social justice conversations with mentors and that having more social justice conversations with mentors was significantly associated with more critical action and perceived inequality. Further, mentoring conversations and sociopolitical efficacy helped to explain the positive role of perceived inequality and action on later attitudes around perceived inequalities and critical action. Qualitative one-on-one interviews of a subset of participants (n = 30) expanded findings from the quantitative data and revealed detailed information about how mentors supported youth critical consciousness. Specifically, mentors engaged in 1) dialogue and reflection, 2) information and resource sharing, 3) nonjudgmental, comfortable conversations, and 4) role modeling. Findings inform the iterative nature of critical consciousness and on how older adolescents leverage support from natural mentors in this process.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".