Mentorships and co-op placements as a means of heightening the need for a secondary school diploma to the education of at-risk students.--
Bibliographic record
Abstract
Both educators and politicians appear to be quite concerned about a dropout rate in Ontario's public schools of some 30 percent. With the basic understanding that a high dropout rate is costly both in economic terms and in human terms, something quite obviously needs to be done to reduce the dropout rate in Ontario schools and, in doing so, ensuring Ontario and its graduates an active role in a growing global economy. This study is an exploratory pilot study in that it examined mentoring and the role that mentoring can play in assisting a student in staying in school and graduating from secondary school. Also incorporated in this is co-operative education and the role it can play, through mentoring, in making students aware of lifestyle level of employment, and of the skills necessary to obtain gainful, meaningful employment. In order to gain information on student attitudes, needs and expectations of a mentoring situation, a series of three questionnaires was used. Also, a questionnaire was distributed to the various co-operative education employers. The intent of this questionnaire was to probe the attitudes, needs and expectations of a mentoring situation from the perspective of an employer. The findings of this study indicated that co-operative education and mentoring are a very valuable and useful component in education. There exist certain factors in a co-operative education setting that serve to enhance and to augment the traditional or "theoretical" setting of the classroom. In addition, a mentoring situation tends to add a sense of relevance to education that students seem to require. Also, an opportunity is offered that allows a student to practice and further refine the skills that have been taught over the course of the student's academic life. Results from this study suggested that a mentoring situation, occurring through a co-operative education situation, adds relevance and a sense of "application" to the traditional or classroom schooling situation. The whole idea of mentoring bodes well for the future of education and of the student. Many advantages are identified in a mentoring situation. One of the advantages is that the schools are able to work quite closely with the community and business in order to stay current and informed on the needs and expected needs of the business community. Co-operative education has now gone beyond being an "experimental" mode of education. All students can benefit from being involved in the program. Certainly at-risk students are aided with staying in school. Those students who are said to be not at-risk can also benefit from being enrolled in the program by gaining hands-on work experience and some of the necessary skills to ensure a place in a growing world economy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.014 |
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".