Weaving Mediation and Embodiment: The Media Ethnographer as Figurations of Mediation
Bibliographic record
Abstract
Building on previous ethnographic approaches, we propose a framework to describe and analyze how media ethnographers are themselves constituted in relation to processes of mediatization. Drawing from mediatization theory, we advance a twofold conception of the media ethnographer as being composed by interweaving processes of embodiment and mediation, which we refer to as figurations of mediation. Using a fourfold typology, we show how different kinds of figurations of mediation establish the media ethnographer’s relations to the field, to research participants, and to research instruments in different ways. We argue that this framework affords media ethnographers the conceptual and methodological tools required to empirically observe and describe how the media ethnographer shifts from compositions through, in, of, and with media. Finally, we demonstrate how this framework can be operationalized by applying it to a case study of startup workers in Vancouver that involves the online platform Meetup.
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 | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.010 | 0.060 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".