MétaCan
Menu
Back to cohort
Record W6927483692 · doi:10.34616/fs.19.2.108.115

The Case of Poland: Encouraging Human Geography through Lesbian Studies

2019· article· en· W6927483692 on OpenAlexaboutno aff

Bibliographic record

VenueUniwersytet Wrocławski · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geography and Geographical Thought
Canadian institutionsnot available
Fundersnot available
KeywordsLesbianHuman sexualityTranscription (linguistics)Meaning (existential)Presentation (obstetrics)Intersectionality

Abstract

fetched live from OpenAlex

What follows is a direct transcription of the conference paper that I gave during the very prestigious Annual International Conference 2018 of the Royal Geographical Society (with the Institute of British Geographers). It took place at the Cardiff University, Wales, UK, on 28-31 of August, 2018. I gave this presentation within the very same panel session that I organised together with Kath Browne from the Maynooth University in Dublin, Ireland, and Catherine J. Nash from the Brock University in Canada. Our session, which I was also honoured to chair, was titled Engaging Contemporary Sexual-Gendered Realities: Geographies of Feminisms, Sexualities, and Beyond1 . Five presentations were part of the panel, including mine. The 20-minute paper was fortified with a PowerPoint presentation, which, of course, is irrelevant to the purposes of the transcription herein. Even though I have decided to keep the title of this transcription in compliance with the title of that presentation, its potential and meaning is much greater. Thinking of a proper academic article that I could develop based on that paper, I would probably make it a point to emphasise the significance of the intersections between sociology and geography, and how they affect my local ambitions to introduce (into the Polish academia) geographies of sexualities on the one hand and interdisciplinary lesbian studies on the other. The paper presented below reflects on the implications of this experience and stance of mine.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.350
Teacher spread0.322 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueUniwersytet WrocławskiSame topicHistorical Geography and Geographical ThoughtFrench-language works237,207