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Record W4410316615 · doi:10.32920/ifmj.v4i1-2.1950

Defining “Done” in Oral History and Interactive Documentaries

2024· article· en· W4410316615 on OpenAlexvenueno aff
Kathleen M. Ryan, David Staton

Bibliographic record

VenueInteractive Film and Media Journal · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOral historyHistoryVisual artsArtArchaeology

Abstract

fetched live from OpenAlex

What does it mean when we say a project is done? It’s a provocative question frequently part of oral history and digital humanities discussions; at Oral History Association meetings in the United States, mini-workshops are routinely held asking what done looks like. One model could focus on fieldwork, such as interviewing everyone available who was involved in a particular phenomena — or at least a critical mass. At this point, the fieldwork phase of a project might be considered to be done.But what about the post-fieldwork phase? Is a project done when that journal article is written? A book published or documentary screened? Or perhaps the marker might be a virtual reality exhibition, the establishment of an online archive, or the completion of an interactive media space. Each of these elements could be construed as a sign of a project reaching its logical concluding point. Here we want to attempt to address the phenomenology of what we are dubbing “doneness,” or the concept of when a project is completed, using two specific projects as examples. Each was conceived as a interactive documentary (i-doc), or a space where co-creation of meaning is prioritized (Aston, Gaudenzi, and Rose 2017), and developed using feminist oral history practices of shared authority (Chase and Bell 1994). The harmony and disharmony found within the process offers practitioners and scholars insights into the practicality of the concept of “doneness.”While the i-doc is still a developing format, there are some broad parameters as to what the form is. The working definition is open-ended, including “any project that starts with the intention to engage with the real, and that uses digital interactive technology to realise this intention” (Aston, Gaudenzi and Rose 2017, 3) including online, virtual reality, augmented reality, and interactive installations. Our own creative practice recognizes how some key facets of the i-doc mesh with foundational practices of feminist oral history, in specific, its focus on strategies of co-creation between researcher/project creator, narrators, and audiences. Here, co-creation may mean different things depending upon the positionality of the individual While audience members may not contribute content, they have agency to shift the meaning through their understanding and experience of the interactive project. Narrators, by contrast, may work more closely with the project creator to develop and frame the meaning of content. The i-doc’s flexibility and experimentation in form is “characterized by interdeterminancy, community, and risk” (De Michiel and Zimmermann 2020, 356) It’s also plagued by technological challenges — what happens when technology becomes obsolete or dies and how does that contribute to a project’s conceptualization of completion? With this in mind, in this paper we offer a working definition of doneness based upon our own practical experience and research from both the open sciences (Humphreys et al 2021) and the digital humanities (Sewell 2009). We also consider the three participants in co-creation found in i-docs: the researcher, the narrator, and the audience. In it, we offer a starting point to answer the question: “are we done?”

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.007
Science and technology studies0.0120.065
Scholarly communication0.0260.026
Open science0.0020.012
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.021
GPT teacher head0.258
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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