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Using S&T foresight to augment organizational tool kits: a Canadian institutional‐entrepreneurial experiment

2004· article· en· W3123937234 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueR and D Management · 2004
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFutures studiesKnowledge managementManagementPolitical sciencePublic relationsBusinessComputer scienceEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper will explore recent Canadian federal experience in developing S&T foresight and creating knowledge sharing networks aimed at creating integrative capacities and convergent domains that involve fusions of several disciplines. More specifically, the paper will report on the experience of the Office of Technology Foresight (OTF) at the National Research Council of Canada (NRC) and its federal partners (science based departments and agencies – SBDAs) as they carried out a major S&T Foresight Pilot Project (STFPP) to elaborate prospective R&D opportunities and challenges in preparation for contingencies that may have to be confronted in the 10–20 year time horizon of 2015–2025. STFPP reports are posted at: http://www.techforesight.ca

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.229
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it