Bibliographic record
Abstract
The purpose of this project was to identify changes in the ecological, socio-cultural and economic life of selected rural municipalities over several years; to evaluate impacts of econo mic activ ities' on the observed changes; to assess how the observed changes have affected the communit ies' standard of living and their environ ment, and to identify their priorities. Data for the analysis was collected fro m the participants through a combination of survey, reports, soil and water sample analysis, and focus group meetings. Results fro m the study revealed that the towns are suffering fro m environ mental pollution such as noise, odour, and soil and water contaminations fro m past and present economic activit ies. Other problems include stunted growth due to declining industrial/commercial act ivities, flooding, and dissatisfactory intergovernmental relationships. Transformation fro m bedroom co mmun ities to commercially thriving municipalit ies, solving environmental pollution created by past economic activ ities in the area, and engaging various demographic groups in town to participate in socioeconomic and environ mental sustainability projects are among the identified prio rit ies of the communit ies under study. This identification of specific causes of stunted growth, and articulation of priority issues to be tackled for attain ment of sustainable growth in the seven participating towns in Southern Alberta would facilitate finding effective solutions to address specific problems in those communit ies.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".