How is the Traditional Canadian Value of Volunteering Surviving?
Bibliographic record
Abstract
The aim of this thesis is to test and consequently disprove or confirm the hypothesis that with the large influx of immigrants to Canada, volunteerism might not be able to survive in its present form. In the theoretical part of the work focus has been set on term definition and volunteering classification because it is a structured activity with its own rules and policy. History of volunteering has been described in the following chapter. This part goes beyond the history of volunteering in Canada since it is a deeply rooted Anglo-Saxon tradition which had been brought there by the British and French. The last chapter has been dedicated to the current situation of volunteering in Canada including a profile of a volunteer and possible current threats. The practical part has been based on a survey conducted among York University community members and an analysis of their answers. This survey became, together with my visit to the 2011 Toronto Volunteer Fair and an in-depth interview, the main source for the comparison of practice and theory.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".