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Record W2780415708 · doi:10.11143/fennia.66683

Reclaiming value from academic labor: commentary by the Editors of Human Geography

2017· article· en· W2780415708 on OpenAlex
John C. Finn, Richard Peet, Sharlene Mollett, John Lauermann

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFennia · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsPublishingPublicationValue (mathematics)Media studiesPublic relationsSociologyPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

There have long been discussions about the need for an alternative publishing model for academic research. This has been made clear by the September 2017 scandal involving Third World Quarterly. The editor’s deeply problematic decision to publish an essay arguing in favor of colonialism was likely meant as click-bate to drive clicks and citations. But we should not lose sight of the fact that this latest scandal is only one recent manifestation of a long-simmering problem that has periodically commanded significant attention in the academic literature, blogs, email lists, conference sessions, and the popular press. As a direct result, over the last decade or more, new journals have been created that specifically endeavor to offer routes around corporate/capitalist academic publishing, and several existing journals have removed themselves from this profit-driven ecosystem. In this commentary, the editorial team of the journal Human Geography weighs in on what we see as the nature of the problem, what we are doing in response, what our successes have been, and what challenges remain.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.332
Teacher spread0.310 · 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