The artist in the field: investigating tourist performativity and ethnographic methodology through art practice
Bibliographic record
Abstract
This research centres on an artistic exploration of ethnographic methodologies whilst investigating tourist performativity and the presentation of self within tourist documentation. Central to this presentation is the performance of the documented smile. The materiality of this research comes from documentary evidence (video, sound, photography, interviews, fieldnotes and diaries) recorded during a fieldtrip around popular tourist destinations in Europe. Data gathering methods, such as participant observation, reflexive writing and informal interviews with tourists, were employed not just to capture the tourist experience of others, but also to explore the multiplicity and variability of the researcher self within the field. The representation of the researcher within the research findings has become one of the issues that this project has sought to address. Two practical outputs, a primary case study entitled Smile: Formaggio con Queso (a randomly configuring computer networked installation) and a secondary case study (an interactive kiosk), interface a database constructed from the field data. Both case studies support research into how ethnographic methods might be used to inform the production processes of an art project, and, additionally, how digital art practice might contribute to the presentation of post-paradigm ethnography. The practical issues of data collecting and the implications of using the self as part of the data source are highlighted. This will be of interest to artists working in field environments where the self and 'other' is synonymous. Furthermore, the primary case study challenges conventional representational ethnographic modes in order to facilitate new kinds of qualitative and ethnographic insights. A reflexive autoethnographic approach to writing the thesis has been utilised to validate my personal narrative as a line of inquiry.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".