Gender inequality in the Nordic film industry: Exploring above-the-line positions in film production
Bibliographic record
Abstract
Abstract In this article, we explore the enduring barriers to gender equality in the Nordic film industry, with a focus on positions of power and structural biases. Despite considerable efforts over the past decades to highlight gender inequality – resulting in more women in creative positions in Sweden, Denmark, and Finland – a significant gap remains. Our analysis of 1,070 films produced and released theatrically between 2010 and 2020 in Denmark, Finland, Iceland, Norway, and Sweden shows men dominating directing, writing, and producing roles in 75 per cent of the cases, with women slightly more present in producing. The study finds a negative correlation between the dominance of men in producing roles and the presence of women in directing and writing roles. Factors such as the size of the creative team and co-production had less impact on the proportion of women in key creative positions than expected, whereas a higher proportion of women in managerial roles is linked to an increased presence of women in positions of directing (Sweden) and writing (Finland). These results indicate that while some progress has been made, structural barriers still significantly hinder gender equality in the industry.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".