The Lighthouse; an interactive documentary. The application of user centred, responsive and interactivity design theory and practice to the case study of the Lighthouse Interactive Documentary
Bibliographic record
Abstract
This practice-led research provides documentary filmmakers with a theoretical and practical basis to understand and design for interactive documentary in the digital medium. This project contributes to the fields of interactive documentary, documentary and interactivity design. This study is centred on the design of the Lighthouse Interactive Documentary that articulates the delivery program and methods of the Lighthouse Foundation, a not-for-profit organisation. The site is primarily designed for specific users, to enable social change in the area of youth welfare and housing. The study focuses on the interactive documentary form within the context of networked and software driven computational devices. The aim of my research is to provide traditional documentary filmmakers like myself with a theoretical framework and methods to design for this environment which interactive designer Janet Murray (2011) names 'the digital medium'. Murray identifies the affordances of the digital medium as being procedural, participatory, spatial and encyclopaedic. This study examines these affordances in relation to the design decisions available to documentary makers who are using interactive techniques. The study also addresses definitions, types and implications of interactive documentary and the new skills required by the person formerly known as the filmmaker in the design of these projects. My research demonstrates user centred, responsive and interactivity design as an effective response to the needs of the filmmaker moving into interactive documentary design. The literature review provides the historic and contextual overview, including documentary, software and communications theory. The theory and practice of user centred, responsive and interactivity design is then applied to two case studies of interactive websites. One belongs to the Berry Street Organisation and the other is an independent site, Here At Home hosted by the National Film Board of Canada and co-produced by the Mental Health Commission of Canada. Both sites address issues of housing for vulnerable people, including youth. The theoretical framework and findings from the case studies are then applied to my design and analysis of the Lighthouse Interactive Documentary site.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".