MétaCan
Menu
Back to cohort
Record W3021805072 · doi:10.3726/med012018_309

<i>Pleasure in the Middle Ages</i>, ed. Naama Cohen-Hanegbi and Piroska Nagy. International Medieval Research, 24. Turnhout: Brepols, 2018, xxiii, 383 pp., 10 b/w ill.

2018· article· en· W3021805072 on OpenAlexaboutno aff
Albrecht Classen

Bibliographic record

VenueMediaevistik · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEurasian Exchange Networks
Canadian institutionsnot available
Fundersnot available
KeywordsPleasureMoresAestheticsSociologyPerspective (graphical)PsychologyPhilosophyArtLawPoliticsVisual artsPolitical science

Abstract

fetched live from OpenAlex

The term ‘pleasure’ has many different meanings, and can be understood both in physical, emotional terms and in religious, or philosophical contexts. Pleasure pertains both to the body and to the spirit, so it turns out to be a very malleable concept which cannot be easily examined in a cultural-historical framework. The contributors to the present volume, however, who originally presented their studies orally at the 2013 International Medieval Congress at Leeds, pursue, as the two editors formulate it themselves, very diverse approaches, depending on their individual research discipline. However, pleasure is regularly associated with emotions, whether from a historical, theological, philosophical, art-historical (only one study), or literary (practically left out) perspective. Of course, this opens another Pandora’s box since ‘emotions’ represent a vast range of aspects in human life that are commonly not easy to identify or to determine in a critical fashion. Cohen-Hanegbi (Tel Aviv University) and Nagy (Université du Quebec à Montréal) offer the approximate definition of pleasure as being “an affect sustained by the interaction between physical and sensory knowledge, between cultural and social mores, and between religious thought and ethics” (xix). It might be difficult to grasp what they really mean by this, especially because they consider such features as “pleasured bodies, didactic pleasures, and pleasure in God” (ibid.), which again leaves us groping for straws. However, we are assured at the end of the introduction that all contributors, despite vast differences in their methodologies and materials, “attempt to define and analyze pleasures, joys, enjoyments, and delights through the language and mindset of the source material” (xxii).

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.004

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 head0.110
GPT teacher head0.366
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMediaevistikSame topicEurasian Exchange NetworksFrench-language works237,207