Learning from past stories of success: values, skills, and attitudes as key determinants of first year postsecondary education completion among Nunavimmiut in Montreal
Bibliographic record
Abstract
Postsecondary Education (PSE) is a key determinant of health. Despite evidence of academic ability, Indigenous youth have the lowest PSE attainment rates of any other cultural or ethnic group. While there is a growing body of literature on barriers to graduation for Indigenous students, many institutions continue to struggle with how best to retain first year students—a critical year in setting the foundation to graduation. This is in part driven by limited research on determinants or strategies for success. Looking retrospectively at the experiences of Nunavimmiut students in their first year through semi-structured interviews and through textual analysis of public Facebook® posts, this thesis adopts an asset-based approach and identifies three key determinants for first year completion—values, skills, and attitudes. Values were elements of the PSE experience which were meaningful to students and included factors such as personal growth and healing, whereas skills were tools and competencies for success such as study skills and goal setting. Attitudes were ways of thinking or feeling towards PSE such as fostering a sense of belonging. For existing student services or those just starting out, this study provides a road map for increasing Indigenous student retention in the first year. It does this through identifying both three broad concepts supporting student success as well as concrete actions within each area which have proven helpful to past students. In addition, this study found that values, skills, and attitudes supported retention through helping students build a ‘sense of place’ in the PSE environment. These findings may prove useful to addressing student retention by reframing the issue as a question of “what builds sense of place on campus?” This project was approved by the Research Ethics Committee of Nunavik’s school board, Kativik Ilisarniliriniq, McGill University, and John Abbott College
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".