Student Labour and Major Research Projects
Bibliographic record
Abstract
This essay cluster addresses major Digital Humanities projects from the perspective of the graduate-student research assistants that work on them, focusing on practical and ethical questions about how DH relies on student labour. Cumulatively, this cluster asks how DH projects with feminist aims might integrate those aims into their own practices. Anna Mukamal’s essay reflects on and theorizes how her role as Project Manager has provided opportunities for mentorship and collaboration outside of the traditional structures of academic supervision. In Mukamal’s experience, the intergenerational and inter-institutional collaboration the Modernist Archives Publishing Project (MAPP) requires has allowed her to foster connections and knowledge that supplement and are adjacent to her graduate coursework and research. Kate Moffatt and Kandice Sharren use their experiences recovering women’s largely invisible labour in the eighteenth-century book trades for the Women’s Print History Project as a framework to consider what kind of labour might be rendered invisible by large-scale DH work. Their essay focuses on two types of work at risk of being overlooked: the work that goes into confirming an absence of data and the affective labour that goes into developing a team of research assistants. Claire Battershill responds to these essays by offering the perspective of a co-director of a major project that relies on student labour. Résumé Ce regroupement de dissertations aborde des projets majeurs des Humanités numériques du point de vue des assistants de recherche étudiant de cycle supérieur qui travaillent sur ces projets, en se concentrant sur des questions pratiques et éthiques concernant la façon dont les humanités numériques s’appuient sur le labeur d’étudiants. Ensemble, ce regroupement demande comment des projets des humanités numériques avec des objectifs féministes peuvent intégrer ces objectifs dans leurs propres pratiques. Dans sa dissertation, Anna Mukamal réfléchit et théorise sur la façon dont son rôle comme Gestionnaire de projet a fourni des opportunités pour du mentorat et de la collaboration hors du cadre traditionnel de supervision académique. D’après les expériences de Mukamal, la collaboration intergénérationnelle et interinstitutionnelle que nécessite le Modernist Archives Publishing Project (Projet de publication d’archives modernistes) lui a permis d’entretenir des connections et connaissances qui enrichissent et qui sont liées à ses études supérieures et à sa recherche. Kate Moffatt et Kandice Sharren se servent de leurs expériences dans la récupération du labeur largement invisible fait par des femmes au dix-huitième siècle dans le domaine de livres pour le Women’s Print History Project (Projet de l’histoire de publication par des femmes) comme cadre pour considérer quelle sorte de labeur peut être rendue invisible par le travail à grande échelle des humanités numériques. Leur dissertation se focalise sur deux types de travail en danger d’être négligés : le travail investi dans la confirmation d’un manque de données ainsi que le labeur affectif investi dans le développement d’une équipe d’assistants de recherche. Claire Battershill répond à ces dissertations en fournissant la perspective d’une co-directrice d’un projet majeur qui dépend du labeur d’étudiants. Mots-clés: gestion de projet; humanités numériques (HN); archive numérique critique; pratique feminist; labeur d’étudiants; pédagog
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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 | 0.021 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.031 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".