Planning [in] the process for multiplex sports facilities : integrating and empowering the "public" in public-private partnerships
Bibliographic record
Abstract
as the central unit of account, it is not about particular individuals per se; reports focus rather on the various patterns, or clusters, of attitudes and related.behaviour that emerge from the interviews" (Hakim, p.26).Hakim also mentions that one of the great strengths of qualitative research is the validity of the data collected: "lndividuals are interviewed in sufficient detail for the results to be taken as true, correct, complete and believable reports of their views and experiences" (p.27).As this study is not concerned with the frequency of phenomena, but rather is an exploration of processes, qualitative research methods are appropriate.The research methods chosen to conduct this study are case study research, interviews and surveys. Case Study ResearchCase studies can be one of the most useful research methods in social inquest and analysis, and "are probably the most flexible of all research designs (Hakim, p.61).lts success can often be measured by how it is applied: "lt's best use appears to me to be for adding to existing experience and humanistic understanding" (Stake, 1995, p.24).Gillham (2000) states that a 'case' can be an individual or a group; it can be an institution or facility; and it can even be a profession or community.A case study, he denotes, is one that investigates these cases to answer specific research questions.ln my research, the case studies will explore the gaps in the public participation process for two public- private paftnerships.While the review of documents, reports and articles will form an integral part of the data collection process, interuiews proved to be highly valuable. lnterviews as a Qualitative Research Methodlnterviews provide in-depth information about a particular research issue or question.Although they can be time-consuming, particularly during the transcription and analysis that follows, interviews can be a highly valuable method in case study research.According to Gillham (2000), "interyiews of one kind or another are indispensable in case study research" (p.59)For the purpose of this practicum, interviewing was chosen because it offered the best and most practical way to obtain the needed data.lnterviews give a sense of 'quality'that cannot be achieved through a questionnaire or survey."The oven¡uhelming strength of the face{o-face interview is the 'richness' of the communication that is possible" (p.62).Qualitative interviews are those that lean towards a more'unstructured' approach.A semi-structured approach was most appropriate for this study.Semistructured interviews are "the most important form of interviewing in case study research [and ifJ well done, it can be the richest single source of data" (Gillham, p. 65).ln a semi-structured interview, "questions are normally specified, but the interviewer is more free to probe beyond the answers in a manner which would often seem prejudicial to the aims of standardization and comparability" (May, 1993, p.93).As opposed to a 'structured' questionnaire, semi-structured interviews often have a predominance of open-ended questions.This type of interview allows for a more in-depth understanding of issues and perspectives.lt ' They were chosen because of their experience, and the likelihood that they would be responsible for the public participatory process in their community.
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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 | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.022 | 0.018 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".