Community, inclusivity and context: Exploring the factors that shape cultural policy in Iran
Bibliographic record
Abstract
Background: Cultural policy are highly context dependent and shaped by local communities and cultural values.Although existing studies focus on cultural policy in Western contexts, there is a need for more research on regions, countries, cities and communities within the Global South, such as Africa and the Middle East.Objectives: The article explores the co-production of cultural policy in Iran at different scales highlighting processes of inclusivity and community involvement at the stages of planning and implementation.Method: This research draws on qualitative data from multiple qualitative sources, informed by the positionality and experience of the first author who has lived, studied and worked in Iran for over 30 years.The experience involved four projects: (1) exploring culture-led regeneration in Rasht city, Iran; (2) reviewing a 10-step bottom-up community-led regeneration scheme ; (3) surveys with 128 users of cultural places and creative activities in Rasht city, Iran and (4) 20 semi-structured interviews with key informants in public institutions.Results: The top-down policies and practices of the Iranian government undermine participatory processes, democratic values and cultural citizenship.Yet, there is also evidence that the cultural identities and practices of local communities remain visible and vibrant. Conclusion:The article demonstrates how policies in the post-revolutionary period limit Iran's adoption of cultural models while suppressing forms of community participation and democratic values.Contribution: The article nuances our understanding of the gap between the universal model of cultural policy and what happens in practice.The understudied case of Iran, the article also highlights how cultural policy, in non-Western contexts, is shaped by a range of factors including cultural values and political imperatives.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".