The nature and extent of foresight-infused strategy: a case study highlighting the liberal arts academy’s future move from traditional education
Bibliographic record
Abstract
Purpose Over the past seven years within a small, liberal arts (LA) Canadian university, significant paradigm shifts in students’ programmatic choices have occurred reflecting student preference for business-related programs versus traditional LA offerings. Grounded in strategic foresight (SF) practices, this paper aims to investigate drivers of declining traditional LA enrolment that are currently a boon for management studies, positing implications for long-term futures of the LA Academy. Design/methodology/approach This paper lays out foundational research exploring phenomena in the academy, including disruptive forces, and explores how SF can clarify and shape long-term choices. Seeking to answer what paradigm-shifting forces really mean for the future of the academy, a case study approach is used to interpret disruptions to a Canadian institution facing present challenges and an uncertain future. Scenarios are developed for the broader academy using an environmental understanding to better inform predictive actions envisioned in academic institutional future planning. Findings The outcome of this research, including four scenarios, will be used to better understand student and stakeholder motivations informing future academic planning. As institutional paradigms appear resistant to change, these foresight-inspired findings are valuable considerations for institutional administrators, particularly those at stressed organizations facing unsettling realities. Originality/value The case study identifies that for the LA Academy, myriad future unknowns exist, including its continued existence in today’s form. Institutions are generally unresponsive to the precursors of future change and are not systematically exploring future options.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.015 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".