The Great Divide: Economic Development Theory Versus Practice-A Survey of the Current Landscape
Bibliographic record
Abstract
As a scholarly field, economic development is a theoretical exploration with very real implications for place. As a practice, economic development is an essential component of local policy and governing and a perceived driver of success and vitality for cities and regions alike. The notable distinction between practice and theory may explain the lack of scholarly consensus and the ambiguity in effectiveness of the practice of development. Using a three-tiered approach, we undertake a comparative analysis of the way in which practitioners and scholars undertake economic development. Through a study of Economic Development Quarterly journal keywords and a review of nine cities’ economic development initiatives, we assess the most frequent topics and initiatives within the discipline. Using the International Economic Development Council best practice awards, we look at what is generally viewed as “successful.” We conclude with an assessment of the general development landscape, considering implications to our findings.
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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 | 0.018 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.027 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".