Bibliographic record
Abstract
The Career-Life Planning Model for First Nations People (1997) was created by Drs. Rod McCormick and Norm Admundson to address the need for more culturally sensitive career planning with First Nations people. The most unique thing about this model is the inclusion of many cultural practices, such as: opening and closing prayers, the invitation to smudge, use an eagle feather or a traditional talking stick, as well as sharing the process with family and friends. The model is based upon traditional cultural beliefs and values that honor connectedness, harmony, balance, gifts, roles and responsibilities, and the importance of family and community. It is a holistic career and life planning tool for First Nations youth, their families and communities. It is an interactive and culturally respectful model that is a welcomed addition to the repertoire of any practitioner. (Author) Reproductions supplied by EDRS are the best that can be made from the original document. Career-Life Planning With First Nations People Kathy Offet-Gartner Mount Royal College Calgary, Alberta, Canada U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) O This document has been reproduced as received from the person or organization originating it. 13 Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
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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 | 0.003 | 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 | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".