Figurations of Digital Practice, Craft, and Agency in Two Mediterranean Fieldwork Projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Archaeological practice is increasingly enacted within pervasive and invisible digital infrastructures, tools, and services that affect how participants engage in learning and fieldwork, and how evidence, knowledge, and expertise are produced. This article discusses the collective imaginings regarding the present and future of digital archaeological practice held by researchers working in two archaeological projects in the Eastern Mediterranean, who have normalized the use of digital tools and the adoption of digital processes in their studies. It is a part of E-CURATORS, a research project investigating how archaeologists in multiple contexts and settings incorporate pervasive digital technologies in their studies. Based on an analysis of qualitative interviews, we interpret the arguments advanced by study participants on aspects of digital work, learning, and expertise. We find that, in their sayings, participants not only characterize digital tools and workflows as having positive instrumental value, but also recognize that they may severely constrain the autonomy and agency of researchers as knowledge workers through the hyper-granularization of data, the erosion of expertise, and the mechanization of work. Participants advance a notion of digital archaeology based on do-it-yourself (DIY) practice and craft to reclaim agency from the algorithmic power of digital technology and to establish fluid, positional distribution of roles and agency, and mutual validation of expertise. Operating within discourses of labour vs efficiency, and technocracy vs agency, sayings, elicited within the archaeological situated practice in the wild, become doings, echoing archaeology’s anxiety in the face of pervasive digital technology.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 it