Host and non-host resident awareness and perceptions of legacies for the 2010 Vancouver Winter Olympic Games
Bibliographic record
Abstract
Given the large investment among host cities, the question about legacy program creation and management becomes important. Creating and managing such programs that benefit residents should derive from the examination of prominent legacy aspects among residents of the host country (i.e., host/non-host city) over time (pre-, during, and post-event). This study aimed to understand and describe host and non-host residents’ perceptions regarding dominant legacy themes and residents’ awareness of specific legacies before, during, and after the 2010 Vancouver Winter Olympic Games. Results indicated that before and during the event host residents identified the material, tangible, and direct legacies. Non-host residents identified the non-material, intangible, and indirect legacies. Post-event, residents identified the non-material, intangible, and indirect legacies. In terms of residents’ awareness of specific legacies, host residents were most aware of the intangible and indirect legacies. Non-host residents were most aware of the potential debt and cost of hosting the Olympic Games.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".