Challenges to Creating Impact in Humanities and Social Sciences in Iran: A Grounded Theory Analysis
Bibliographic record
Abstract
Aim: Increasingly, researchers and universities are demanded to demonstrate the relevance of their publicly funded research projects to societal challenges and development. This societal contribution is referred to as research impact in Iran. The primary purpose of the present study was to evaluate the challenges of creating research impact in Social Sciences and Humanities (SSH) in Iran’s context. To do so, we investigated participants' viewpoints from the research community and potential research users. Methodology: This was a qualitative study with an explanatory orientation to address the study aim. Participants were SSH researchers and research managers at Iranian national universities as well as representatives of governmental organizations that had direct roles in the production or the use of research results. We used purposeful snowball sampling to identify participants with relevant knowledge and experience. Accordingly, we carried out semi-structured interviews with 16 participants. For analyzing the data, the grounded theory method was used, and then a final theory was formed. Findings:Data from the interviews represented broad challenges in the process of research to impact. Specifically, these challenges were classified into six categories, namely, the core phenomenon, causal, contextual, and intervening conditions, strategies, and consequences. Each of these categories relates to a different aspect of challenges that researchers or potential users face in knowledge mobilization and uptake of research evidence. Conclusions:The study revealed that the main obstacle to creating research impact in SSH in Iran is the lack of a definition for knowledge mobilization that is appropriate to SSH research. The current definitions and structures in universities are not consistent with the characteristics of SSH research and its audience. Furthermore, since this definition is not consistent with the nature of SSH research, researchers do not receive the necessary incentives and support for this purpose and are not able to integrate knowledge mobilization activities with their current academic activities and responsibilities. These findings emphasize the role of universities in facilitating the impact creation process by employing appropriate definitions and structures for knowledge mobilization.
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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 | 0.035 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".