The Role of Expectations of Science as Promissory Discourses in Shaping Research Policy: A Case Study of the Creation of Genome Canada
Bibliographic record
Abstract
This thesis examines promise of science discourse and its impacts in shaping research policy. Through a single case study of the origins of Genome Canada, the research was guided by the question: How did expectations of genomics, as promise of genomics discourse, shape the creation of Genome Canada? Background is presented on the long-standing, but largely unacknowledged, relationship between the promise of science and research policy. Theoretical grounding for the study is provided by concepts from the discursive policy analysis and sociology of expectations of science and technology literatures. Promise of genomics discourse, expectations of genomics of story-lines and a conceptualization of knowledge-based discursive power provide the theoretical and analytical basis for an in-depth examination of the ideational effects and material impacts on research policy decisions over three years (1997 – 2000) that sought to position Canada as a leader, internationally, in genomics research. As discourse, the promise of genomics fulfilled an essential role in shaping policy decisions. The promise of genomics discourse and expectations of genomics story-lines functioned in a complex interplay of discursive practices and dynamics among diverse policy actors within a promise of genomics discourse-coalition to produce a range of ideational and material impacts. The promise of genomics discourse produced powerful promise of genomics subject-positions from which policy actors perceived their interests, identities and preferences and gained agency, which led to various material impacts, including the transformation of Canada’s research policy framework. The thesis derives valuable insights about how the diverse policy actors involved in the research policy process perceive and are influenced by the promise of science. With the increasing importance of research policy to a range of broader policy priorities underpinned by expectations that science will resolve societal challenges and contribute to socio-economic benefits, this thesis sheds light on how complex research policy decisions are made; it further contributes to understanding the processes that lead to those decisions that increasingly must reconcile the relationship between science and society.
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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 | 0.027 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.057 | 0.044 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".