‘Go fish’: Conceptualising the challenges of engaging national web archives for digital research
Bibliographic record
Abstract
Abstract Our work considers the sociotechnical and organisational constraints of web archiving in order to understand how these factors and contingencies influence research engagement with national web collections. In this article, we compare and contrast our experiences of undertaking web archival research at two national web archives: the UK Web Archive located at the British Library and the Netarchive at the Royal Danish Library. Based on personal interactions with the collections, interviews with library staff and observations of web archiving activities, we invoke three conceptual devices ( orientating, auditing and constructing ) to describe common research practices and associated challenges in the context of each national web archive. Through this framework we centre the early stages of the research process that are often only given cursory attention in methodological descriptions of web archival research, to discuss the epistemological entanglements of researcher practices, instruments, tools and methods that create the conditions of possibility for new knowledge and scholarship in this space. In this analysis, we highlight the significant time and energy required on the part of researchers to begin using national web archives, as well as the value of engaging with the curatorial infrastructure that enables web archiving in practice. Focusing an analysis on these research infrastructures facilitates a discussion of how these web archival interfaces both enable and foreclose on particular forms of researcher engagement with the past Web and in turn contributes to critical ongoing debates surrounding the opportunities and constraints of digital sources, methodologies and claims within the Digital Humanities.
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 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 | 0.084 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.022 | 0.092 |
| Scholarly communication | 0.044 | 0.051 |
| Open science | 0.007 | 0.030 |
| Research integrity | 0.009 | 0.007 |
| 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".