Exploring factors influencing the retention rates of Indigenous students in post-secondary education
Bibliographic record
Abstract
In comparison to Caucasian students, Indigenous students are outnumbered when it comes to enrollment in post-secondary education programs. Designated seats for Indigenous students often sit empty. With an aim to succeed academically, Indigenous students have had to develop a strong sense of resiliency and identity to overcome barriers to attend institutions of higher learning. Questions still remain as to why the seats are not being filled or what is preventing Indigenous students from enrolling in post-secondary education resonate among faculty and administrative leaders. Tinto’s model of persistence confirmed the importance of integrating social involvement in academia. Students need support to achieve academic success and personal satisfaction. Motivational factors consisting of specific family member encouragement and exploring a better way of life was seen as the main reason to enroll in post-secondary education. Limitations of support at the peer and institutional levels were seen as challenging for Indigenous students and often times had an impact on academic completion. Questions as to why the seats are not being filled or what is preventing Indigenous students from enrolling in higher education programs led to the purpose of this study.
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 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 | 0.002 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".