Volunteer Tutors: Agents of Change or Reproduction? An Examination of Consciousness, Ideology and Praxis
Bibliographic record
Abstract
Volunteer tutors play a significant role in delivering adult literacy programs. It is estimated that up to 60% of all instructors in adult literacy programs in the United States are volunteers (Ziegler, McCallum, & Bell, 2009). However, volunteer tutors’ work or experience are rarely the subjects of research. Volunteer tutors’ contributions to adult literacy are significant because they have personal relationships with learners while being expected to deliver ministry guidelines. In this paper, we examine the narratives of three volunteer tutors from a program in Ontario, Canada, to understand whether and how volunteer tutors act as agents of change or reproduction. Using a Marxist analysis, we review the consciousness, ideology, and praxis of the volunteer tutors in this study. We delve critically into the work of volunteer tutors to illustrate the potential and the limitations of volunteer tutors’ role in bringing about social transformation in the field of adult literacy.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".