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Record W2248830332

Anthropocene U: Academic responses and responsibilities at Lakehead University

2015· dissertation· en· W2248830332 on OpenAlexaboutno aff
Natalie Gerum

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2015
Typedissertation
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsAnthropoceneEnvironmental ethicsEarth sciencePolitical scienceEngineering ethicsGeologyEngineeringPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores the stories of six faculty members and administrators at
\nLakehead University who are responding to the Anthropocene through their academic
\nwork. Their stories suggest that there are barriers facing academic engagement with the
\nAnthropocene and the associated possibilities for action are uniquely empowered by the
\nparticular position and privileges of higher education; rich tensions arise in exploring the
\nresponse-ability of the academy to the Anthropocene. I consider the planetary and
\npedagogical contexts from which this research develops. Then, turning to participant
\nstories, I look to appreciative inquiry, narrative inquiry, and place inquiry to guide my
\ninteractions with their experiences in ways that intend to grow the community of scholars
\nresponding to the Anthropocene at one Canadian university, Lakehead University in
\nThunder Bay, Ontario. I next introduce the participants and the site of research through a
\nseries of vignettes, and explore the experiences of participants as they work to respond to
\nthe current moment on the planet. Their stories begin to illustrate the parallels between
\nhow neoliberalism has helped usher in the Anthropocene and has shaped the university in
\nways that minimize its ability to respond. The final chapter speaks to possibility and
\npresents participants? visions for a University more responsive to the Anthropocene,
\nillustrated by photographs of places that reflect participants? understandings of what is
\npossible and that integrate place-voice into the research. This thesis concludes by
\nsummarizing key themes, and by daring readers to consider their own response-abilities
\nin the Anthropocene.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.284
Teacher spread0.258 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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