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Record W2082561485 · doi:10.1353/scp.0.0074

Sticker Shock and Looming Tsunami: The High Cost of Academic Serials in Perspective

2010· article· en· W2082561485 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Scholarly Publishing · 2010
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingRecessionProductivityShock (circulatory)Perspective (graphical)Public relationsGreat recessionPolitical scienceBusinessEconomicsEconomic growthLawComputer scienceMacroeconomicsMedicine

Abstract

fetched live from OpenAlex

Recession is currently causing a resurgence of the academic serials crisis. Profit-mongering by commercial publishers is once again denounced as the key driver of the crisis. However, a critical analysis of institutional and bibliometric data does not reveal excessive corporate greed in recent years; instead, it suggests that the present hurdles stem largely from years of inadequate budget allocations to academic libraries and from a publishing frenzy fuelled by simplistic methods of evaluating faculty productivity. To prevent what is likely to be the publishing equivalent of a tsunami in the next few years, universities and research institutions urgently need to re-emphasize quality over quantity in the publishing process, and they must find ways to include peer-reviewing efficiency among their criteria for productivity and impact. Achieving these goals will require concerted efforts by researchers, librarians, and publishers.

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)0.106
metaresearch head score (Gemma)0.401
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Bibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1060.401
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0310.056
Science and technology studies0.0000.000
Scholarly communication0.0410.048
Open science0.0040.001
Research integrity0.0000.005
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 head0.375
GPT teacher head0.528
Teacher spread0.153 · 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