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Record W3031075648 · doi:10.16997/ahip.6

Walking with a Ghost River: Unsettling Place in the Anthropocene

2020· article· en· W3031075648 on OpenAlexaff
Tricia Toso, Kassandra Spooner-Lockyer, Kregg Hetherington

Bibliographic record

VenueAnthropocenes – Human Inhuman Posthuman · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of TorontoConcordia University
Fundersnot available
KeywordsAnthropoceneHistoryAestheticsGeographyArchaeologyEnvironmental ethicsArtPhilosophy

Abstract

fetched live from OpenAlex

The call to explore a different mode of being-human in what many have termed the Anthropocene, is an invitation to think about what it means to live in place in a more expansive and speculative way. It also asks that we take a different starting point for critical inquiry, and rather than pursue an explanatory end, the approach remains ‘curious, experimental, open, adaptive, imaginative, responsive and responsible’ (Gibson et al. 2015: i–ii). This paper charts the messy, and often faltering methodologies we have developed as a means of thinking through urban landscapes of colonial violence, and engaging with the ghostly forms of past histories in present-day urban places through the multi-sensorial experience of walking. In attending to the many complex connections and relationships between socio-economic, techno-political, and the more-than-human world, we broadened our lens of inquiry to include the multitude of related and interconnected spatial and temporal relationships that came across our path, and sought to develop a mode of ethical relationing with a ghost river.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0050.005
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.036
GPT teacher head0.336
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

Explore more

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