Formal and Informal Training for Workers with Low Literacy: Building an International Dialogue
Bibliographic record
Abstract
The purpose of this exploratory study was to investigate some of the kinds of formal and informal workplace training activities that workers with low literacy engage in from different parts of Canada and the United Kingdom. The study employed a multi-site case study research design with 31 employees and 18 instructors from seven different types of workplace literacy programmes in various regions of Canada and 42 employees and six supervisors/tutors from four workplace basic skills programmes in the north and south of Greater London, England. Data sources from each country were developed and were used for comparable purposes following a within case and cross case analysis. The findings are described under three main themes. The first theme depicts the range of formal workplace programmes in both countries that employees with low literacy have participated in. The second pattern highlights the main types of informal learning activities that emerged from the data which included: observing from knowledgeables; practicing without supervision; searching independently for information; focused workplace discussions and mentoring and coaching. The third theme describes some of the determining factors of the informal learning process. Implications of the study suggest that company sponsored workplace and essential skills programmes act as catalysts for further learning at work. As well, findings also seem to indicate that various forms of self-directed learning and the organisational context may play an important role as these workers engage in and shape everyday workplace practices. Suggestions for continuing the cross nation studies are also discussed.
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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 | 0.021 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".