Implementation of the Alberta Accountability Framework
Bibliographic record
Abstract
In 1994 the government of Alberta introduced legislation that mandated accountability for all government departments, including education. At the same time, the provincial budget cut dollars to education by 12.4%. The message to educators was clear: reduce education costs while retaining and improving education results. The impact of these directives was dramatic. The Alberta ministry of education closed regional offices and reduced staff. School boards, through amalgamations, were reduced in number from 140 to sixty. One intent of the accountability legislation was to align classroom, school and jurisdiction goals with provincial education goals and priorities. The alignment was monitored through Three-Year Plans and Annual Education Results Reports that were submitted to the ministry by school jurisdictions. At the same time, decision-making was decentralized to the school level and site-based administrators were given the responsibility of developing school plans that reflected jurisdictional and provincial education goals. This paper summarizes the development of the provincial accountability framework and reports an action research project that investigated the implementation of this framework from a field perspective. The paper is a synthesis of four papers by different authors. The four papers have been merged to present a more comprehensive story of the development and implementation of the Alberta accountability framework.
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 | 0.066 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".