Bibliographic record
Abstract
The territory of interactive and immersive nonfiction narratives has ignited ideas and expressions for creating varied digital environments and diversifying dialogues. Expanded documentary practices (Takahiko 1966; Kim 2022) flourish as creators and researchers-practitioners continually reimagine their strategies and methodologies. In recent years, there has been a shift toward conceptualizing polyphonic (Aston and Odorico 2018; Zimmermann 2020) digital spaces and decolonizing practice-based research in interactive documentary (Ryan and Staton 2022), resulting in a fertile union of theory and practice. As a practitioner-researcher pursuing a PhD, I investigate the intersection of interactive documentary practices and family archives from the Portuguese diaspora within a practice-based research framework (Vear, Candy, and Edmonds 2022). My practice focuses on personal narratives, memories, and testimonies of Portuguese descendants and their families’ recollections of migratory experiences during the 1960s and 1970s. The interactive documentary Orange in the Pocket, Aerograms, and the Rest of the Memories (2024) incorporates four family archival elements and audible testimonies depicting the fragmentary nature of these remembrances. This paper aims to discuss the development of my interactive documentary practice, Orange in the Pocket, Aerograms, and the Rest of the Memories (2024), focusing on listening to multiple voices throughout the creative work and within the interactive documentary. I propose to examine the artifact through the lens of listening (Rangan 2020; Munro 2019), “listening being” (Lipari 2009), "haptic listening" (Leimbacher 2017), and "affective intermediality" (Pethő 2023) concepts, reflecting on how these concepts and ideas relate to new spheres of dialogue, polyphony, and affective geographies (Chauvin 2019), while perceiving and engaging more deeply with the interactive documentary sphere. Resonances punctuated this making process as I explored encounters between private memories and their collective potential to create a diversified place for exchanging migratory experiences. I suggest that interactive documentary practices create affective tapestries that transform personal interactive experiences into meaningful listening habits and encounters with oneself, others, and the larger context beyond our everyday lives through listening and affective imaginaries, conceivably creating novel webs of polyphonic dialogues.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.025 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".