Bibliographic record
Abstract
Committed documentary practices created with and for people affected by social problems have a long tradition. Today, digital media cultures seem to offer new opportunities for participation, as well as new documentary forms of expression that can give marginalized positions cultural visibility on a global level, while simultaneously promoting exchange between those concerned. This contribution argues that in engaged interactive documentary projects on the web (i-docs), community experiences and counterpublics that respond to social and cultural exclusion mechanisms are closely linked. To collectively demand one’s participation in the public sphere and dominant culture through ‘doing documentary’ can foster the feeling of being part of a (virtual) community. Emerging ‘we-groups’ with democratic goals articulate marginalized positions in the form of counterpublics and seek to address an outside audience with their counterpublic discourses. However, the shared aesthetic practices and communicative narrative processes that underlie the sense of community are not always conducive to socio-cultural participation. This paper examines the relation between demanding one’s socio-cultural participation and community experiences in committed participatory i-docs. The hypothesis is that group-specific goals are difficult to reconcile with promoting the cultural participation of those affected by social problems. The theoretical framework first discusses the prerequisites for socio-cultural participation, including media-philosophical approaches and theories of democracy. In addition, the contribution clarifies what distinguishes a (virtual) community from community experiences. Then, three committed i-docs that promote a sense of community and try to challenge dominant cultural and societal structures serve as examples in this investigation: Dadaab Stories (2013), Question Bridge: Black Males (2012), The G Word: Transforming Gender Norms, One Story at a Time (2015). The study uses media-aesthetic and content analyses of the i-docs as well as praxeological analyses of their processes conducted based on paratexts and interviews. This approach examines community experiences and identifies the potential for counter-narratives that deconstruct stereotypes and disseminate positions that are culturally almost invisible. The three i-docs show that the self-representation of marginalized participants and sharing their experiences can be useful for a sense of community, but are not always sufficient for challenging dominant images and identity attributions. The contribution argues that the reproduction of stereotypical (self-)images, for example, prevents the promotion of cultural participation.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.037 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".