The theory-practice gap: epistemology, identity, and education
Bibliographic record
Abstract
Purpose – The purpose of this paper is to theorize the theory-practice gap and to provide examples of how it currently expresses itself and how it might be addressed to better integrate between the worlds of thought and praxis. Design/methodology/approach – Two empirical examples exemplify how the theory-practice gap is an institutionally embodied social reality. Cultural-historical activity theory is described as a means for theorizing the inevitable gap. An example from the airline industry shows how the gap may be dealt with in, and integrated into, practice. Findings – Cultural-historical activity theory suggests different forms of consciousness to exist in different activity systems because of the different object/motives in the world in which we think and the practical world in which we live. A brief case study of the efforts of one airline to integrate reflection on practice (i.e. theory) into their on-the-job training shows how the world in which pilots think about what they do is made part of the world in which pilots live. Practical implications – First, in some cases, such as teacher education, institutional arrangements can be made to situate education/training in the workplace. Second, even in the training systems with high fidelity, high validity (transferability) cannot be guaranteed. Originality/value – The approach proposed provides a theory not only for understanding the theory-practice gap but also the gap that exists even between very high-fidelity (“photo-realistic”) training situations and the real-world praxis full of surprises.
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.
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 | 0.076 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.012 | 0.130 |
| Scholarly communication | 0.035 | 0.049 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 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".