Work time and learning activities of the continuously employed
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the paid and unpaid work time and learning activities of a small longitudinal sample ( n =286) of continuously employed Canadians over the 1998‐2004 period. Design/methodology/approach A sub‐sample of those who responded to two national surveys carried out in 1998 and 2004 and who were continuously employed throughout this period was selected. In addition to a quantitative analysis of their responses to both surveys, a qualitative analysis of open‐ended interviews in 2000 with many of the same respondents offers further insight into orientations to engagement in formal (course‐based) and informal learning. Findings Those who are not taking adult education courses are still very likely to participate continually in job‐related informal learning. There is some indication that continuing lack of participation in courses may be associated with declining participation in job‐related informal learning. The in‐depth interviews suggest that most continuously employed respondents see course‐based education and informal learning as complementary. Originality/value The lack of prior longitudinal population studies means that understanding of continuity and change in work and learning relations has been based on inferences from cross‐sectional surveys. There are few recent longitudinal surveys of work and learning and none that incorporate both unpaid work and informal learning as well as paid work and adult education course participation. This study provides some elementary benchmarks for further diachronic research on work time and learning relations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".