An exploratory study of the perception of employment generated from the Glasgow 2014 Commonwealth Games by Local Residents.
Bibliographic record
Abstract
This dissertation project was undertaken to assess the Glasgow 2014 Commonwealth Games (GCWG) effect on employment in the City of Glasgow (COG) and how it was perceived by the local residents (LR). The process began by examining studies carried out by the Glasgow City Council, the Scottish Government and other official games partners. Within these studies were the results found from their original research to conclude the impact to employment. Their results were compared to gain a general consensus. However, the main aim for this study was to discover how LR felt employment was impacted. As this research has not been carried out before a comparison of literature on previous mega event impacts to local communities was conducted. The researcher widen the literature review to include social and environmental impacts, along with the economic impact to gain a general view on the effect mega events have on host cities. \nWith this knowledge the researcher then conducted their own primary study. A series of interviews were carried out with business leaders directly involved in the GCWG. The aim for these interviews was to distinguish the impact to the economic stance of the organisation and how it effected employment within their specific organization. This was then compared to the questionnaires completed by LR on how they felt employment was impacted. \nThe study concludes that the officials involved felt very positively about the GCWG and its effect on Glasgow. Not only do they believe it resulted in higher levels of employment for the city but also classed the Commonwealth Games (CG) as a valuable learning experience. The LR were also supportive of the CG and drew to an overall conclusion that the GCWG had a positive impact on employment in the COG. \nHowever, the matter of sustainability received a split vote from LR.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".