Current Administration of Indian Control of Indian Education in Alberta: Implications and Challenges
Bibliographic record
Abstract
This mixed method, exploratory multi-site case study sought to understand the administrative, economic, and political challenges faced by First Nations education directors in Alberta. The purpose was to find out whether (and in what ways) these challenges restrict their capacity to improve the quality of schooling for First Nation children and to identify the roles and responsibilities of education directors who directly administer First Nation schools. The theoretical lens of Tribal Critical Race Theory (TribCrit) underpinned this study. Survey and semi-structured interviews were conducted with 16 education directors in Alberta representing 34 First Nations. This study also found that the processes and procedures put in place, for newly hired education directors to work with, varied between First Nations and were deemed insufficient. Some of the challenges education directors faced included: working with the general education system management, providing instructional leadership; negotiating change; working with a school board, council or oversight body; reporting to a range of internal and external authorities; recruitment and retention of effective teachers; being constrained by federal and provincial mandates, dealing with a perceived crisis in education within First Nation; community pressure for provincial schools to be the preferred schools for students to attend; and support from the parent, community, and agencies for schools was lacking. The most critical and chronic challenge as noted by education directors is the student achievement gap between FN students and other Alberta school students. Also, language and culture programs are not being adequately funded in First Nations. This research revealed that education directors believe First Nations are supportive of Indian Control of Education but perceive the federal government as unsupportive. Critically, the research revealed that the extent and nature of poverty experienced by students affects proper implementation of Indian control of Indian education. Further, the education directors strongly believed that core funding for schooling is grossly inadequate in light of school-based needs. In other words, the failure of the government to provide adequate funding for on-reserve schooling dramatically impeded the capacities of education directors to carry out their roles and responsibilities thereby inhibiting school improvement.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".