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Record W4214920629 · doi:10.4000/belgeo.52842

Disciplinary chasm: questions on identification and mending

2021· article· en· W4214920629 on OpenAlexaff
Cristian Suteanu

Bibliographic record

VenueBELGEO · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsScholarshipPositivismDisciplineMeaning (existential)Value (mathematics)EpistemologyIdentification (biology)SociologyPositive economicsSocial sciencePolitical scienceLawEconomicsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

While the fracture separating human from physical geography is not new, its pervasive presence appears to hurt scholarship even more deeply than in the past. This article formulates questions about the major factors that are responsible for the current separation, and explores realistic opportunities for fracture-healing. The identified obstacles reach beyond the effects of positivism: the paper recognizes the role of differences in the meaning and value assigned to change and time. Nonlinear theory is shown to operate far from the expectations related to positivism, in innovative, fluid ways, both in physical geography and in human geography. Notwithstanding nonlinear theory’s potential to act as a builder of bridges, the article argues that neither this, nor other methodological instruments can mend the disciplinary fracture, as long as the question of the mutual recognition of value is not openly addressed. The resulting renewal and cross-fertilization are worth the effort.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.068
metaresearch head score (Gemma)0.158
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.158
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0080.005
Science and technology studies0.0210.148
Scholarly communication0.0240.064
Open science0.0070.030
Research integrity0.0150.014
Insufficient payload (model declined to judge)0.0080.001

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 head0.045
GPT teacher head0.380
Teacher spread0.335 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBELGEOSame topicGeographies of human-animal interactionsFrench-language works237,207