Insights on the challenges faced by youth in Alberta
Bibliographic record
Abstract
This chapter explores Alberta’s youth labour market by focusing on youth-accessible online job postings (YAPs). YAPs are identified using text-mining techniques applied to job postings that contain specific key words in the job title, like trainee or intern, or that require a maximum experience of one year or less, signalling that youth should be able to apply for these positions. The chapter examines the evolution of YAPs over time, highlighting changing trends. The chapter investigates YAPs across various sectors and career areas, revealing where the opportunities for young individuals may be found. The chapter analyses the required qualifications and degree requirements found in YAPs, and provides insights on what contract types are typically offered to youth. It delves into the transversal and technical skills demanded in the main career areas for youth, identifying the key competencies needed for success. Career transition and retraining pathways are also discussed, outlining potential routes for career advancement and skills development.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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".