Ten Traps for Non-Representational Theory in Human Geography
Abstract
:1. Introduction
- “I guess they got a way of reading my mind/I guess I got to adjust” [1].
2. Non-Representational Theory in Human Geography
2.1. Defining Non-Representational Theory
2.2. Interpreting Non-Representational Theory within Human Geography
3. Ten Geographical Traps for Non-Representational Theory
3.1. The Small Geographies Trap
3.2. The Representation Trap
3.3. The Cognitive Trap
3.4. The Empiricism Trap
3.5. The Detail Trap
3.6. The Access Trap
3.7. The Subjectivity Trap
3.8. The Methodology Trap
3.9. The Translation Trap
3.10. The Process Trap
4. A Worked Example: An Empirical Field Observatory for Human Geographies of Encounter
5. Discussion
6. Conclusions
Funding
Data Availability Statement
Conflicts of Interest
References
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Observable | Underlying Behavior | Supporting Analysis | Available Empirical Data | |||||||
---|---|---|---|---|---|---|---|---|---|---|
C | F | I | L | M | O | P | V | |||
Pose | Action | Action classifier | ||||||||
Intention | ||||||||||
Attention | Gaze direction | |||||||||
Locomotion | Ambulation |
| ||||||||
Footfall | ||||||||||
Cadence | ||||||||||
Kinematics | ||||||||||
Proxemics | Trajectory clustering | |||||||||
Heading | Maneuvering | Time geography | ||||||||
Wayfinding | Map-matching | |||||||||
Personal space | Buffering |
| ||||||||
Object use | Task action | Action classifier | ||||||||
Valence | Affect | Affect classifier | ||||||||
Physicality | Interaction | Segmentation |
Trap | Observation (See Section 3) | Discussion |
---|---|---|
Small geographies | C, I, L, M, O, P, V | The immersive nature of the observations, and their ability to register sensed, coded, and measured properties against high-resolution spatial and temporal increments, allow for very small geographies to be studied. |
Circularity in representation | O, V | This trap is not wholly or satisfactorily avoided. Object recognition from video necessarily relies (exclusively, heavily, and in often biased ways) on representation and categorization relative to pre-baked labels. |
Cognitive | C, P, V | Some signs of recognition or attention could be tied to pose detection from video. Where understood, cognitive factors can also be hand-coded by IPC. |
Detail | C, F, I, L, M, O, P, V | The observation scheme produces large volumes of detail on the human geography of encounter. Moreover, these details can be cross-indexed (via space- and time-based stamps certainly, but also across different empirical categories, as shown in the shaded areas of Table 1). |
Access | C, F, I, L, M, O, P, V | By essentially embedding with individuals in the natural milieu of their momentary activities, the observational scheme presents rather unprecedented access to human geography in applied settings. |
Empiricism | C, F, I, L, M, O, P, V | The observational scheme is highly empirical, using qualitative categories, recognizers, and measurements. |
Subjectivity | V | Although all of the data in the observational scheme are open to subjective interpretation, records of live video mean that that the scenes can be revisited through many different lenses as ground truth. |
Methodology | C, F, I, L, M, O, P, V | The applied observation introduces a wide range of methods for studying NRT in pragmatic terms, using novel mixtures of coded ethnography (IPC), machine learning, geomatics (GPS, LiDAR), and signal processing (IMUs). |
Translation | C, F, I, L, M, O, P, V | Each of the observation instruments and methods can be ported to new locations. Indeed, we applied our study widely across different locations in New York City. We also showed that the scheme can work on any video, including those taken from Online sources (Figure 5). |
Process dynamics | C, I, L, M, P. V | Several of the observations can be time-stamped, so that process dynamics can be localized to snapshot instances of time (and space). Moreover, a number of the methods support streams of time to be studies, particularly via inertial measurement, LiDAR, and video. |
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Torrens, P.M. Ten Traps for Non-Representational Theory in Human Geography. Geographies 2024, 4, 253-286. https://doi.org/10.3390/geographies4020016
Torrens PM. Ten Traps for Non-Representational Theory in Human Geography. Geographies. 2024; 4(2):253-286. https://doi.org/10.3390/geographies4020016
Chicago/Turabian StyleTorrens, Paul M. 2024. "Ten Traps for Non-Representational Theory in Human Geography" Geographies 4, no. 2: 253-286. https://doi.org/10.3390/geographies4020016
APA StyleTorrens, P. M. (2024). Ten Traps for Non-Representational Theory in Human Geography. Geographies, 4(2), 253-286. https://doi.org/10.3390/geographies4020016