Gender, nature and nation: Resource nationalism on primary sector reality TV
Bibliographic record
Abstract
A number of media companies in the United States broadcast reality TV series that chronicle lives, conflicts and economic highs and lows in the primary sector of the economy. This is curious from a cultural standpoint because employment in the primary sector has plateaued, and, in many regions, is in active decline. This paper examines primary sector reality TV series about fishing, logging and mining televised to audiences in the United States by broadcast networks Discovery and National Geographic. Using discourse and visual analysis, we deconstruct prominent nature–society representations in a sample of 100 episodes systematically selected from 15 different series. Three points emerge from the data and are generalizable across the series. First, nearly all characters are male, and storylines suggest that successful men are competitive, strong and brave. Second, hegemonic masculinity is made legible in contrast to a feminized nature that is almost always suggested to be acting against male protagonists. Third, US symbolism is common, and Americans are presented as ideally skilled and situated to exploit natural resources within and beyond domestic borders. Overall, the series mediate a highly gendered nature–society relation that weaves together hegemonic masculinity and resource nationalism. We conclude that viewers – many of whom will have little personal experience of primary sector work – are invited to relate with concern for the ‘real-life’ characters and with anxiety for the future of a specific identity and associated set of labour and consumption practices.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".