Resilience and Educational Pathways: A Longitudinal Analysis of Low Reading Achievers
Bibliographic record
Abstract
Utilizing the first three cycles of the Canadian longitudinal Youth in Transition Survey (YITS), this paper analyses the educational pathways of 6,342 Canadian youth who at age 15 scored below the level considered necessary for effective functioning in a knowledge-based society. The concept of resilience is integrated into a broader sociological framework of acceptance of cultural goals and access to the means for achieving these goals. Within this framework, the multiple effects of two components of resilience on educational outcomes are assessed: a) the availability of social and institutional supports and b) youth’s own attitudes, values and behaviours that enabled some of them to overcome the obstacle associated with their limited reading performance. Multinomial logistic regression was used to show that a variety of possible measures of resilience differentiate between dropping out, completing high school, and participating in postsecondary education. Additionally, some aspects of resilience are more effective for avoiding the worst educational outcome (dropping out) while others appear to facilitate achieving the best outcome (participating in postsecondary education). The paper concludes that resilience is better viewed as a sensitizing than a theoretical concept.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".