Bibliographic record
Abstract
Building upon the ideas of decoupling and convergence, this thesis explores the structure of place-based community experience and levels of well-being for rural residents in southern Alberta.The research objectives are to: 1) measure and identify the experiential character of rural communities within the Behavioral, Cognitive and Affective Domains of community social life, and to understand the structure and complexity of this experience; 2) assess the aggregate differences in the intensity of these experiential structures by degree of rurality as represented by Metropolitan Influenced Zones (MIZs); and 3) model the extent to which these dimensions may account for differences in well-being.Sixteen unique dimensions of variation in rural community experience are identified -partially supporting convergence -and almost no differences are found in the intensity of these dimensions by degree of rurality (MIZs).The findings show a subset of experiential dimensions to be significant predictors of well-being in rural people.v ACKNOWLEDGMENTS First and foremost I would like to thank my family and friends for their unending love, support and encouragement throughout this latest endeavor in my life.Thank you for your understanding and continuous reinforcement, without all of you I would have been adrift on many occasions.It is my belief that a person's worth may be measured by their family and friends; ya'all have proven that I am priceless ;) I would like to recognize my supervisor: Dr. Ivan Townshend; along with my
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".