Bibliographic record
Abstract
This report is the continuation of a previously initiated project, which resulted in the designation of a more environmentally sustainable residence, or ecopod, within the Columbia Lake Townhouses of the University of Waterloo. Though this ecopod will commence in the fall of 2003, no marketing plan for it exists. Satisfying this need is the focus of our study. A good marketing concept is an all consuming process which determines what the consumer wants and needs, then provides it. Therefore, our goal was to determine the mediums through which most incoming students gained information on residences, how many students would be interested in living in a an environmental residence, and how we could market the ecopod effectively. The research question that we sought to answer was, “how can we market the CLT ecopod to encourage environmentally conscious individuals to want to live there?” The methods used to obtain our research objectives included focus group discussions with the University of Guelph eco house residents in order to gain an understanding of the strengths and weaknesses of how their eco residence functions so that we may make educated recommendations on what should be implemented in the CLT ecopod. High school surveys were done in order to understand the needs and expectations of potential ecopod residents. Secondary research included literature reviews of marketing texts and similar projects which have been previously implemented. Based on the results of our research methods we have postulated eight recommendations. These include:
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.545 | 0.560 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".