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Record W2915225699 · doi:10.23912/9781911635062-3977

Introduction to Clubs

2018· book-chapter· en· W2915225699 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueGoodfellow Publishers eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsReputationClubPolitical sciencePleasureLaw

Abstract

fetched live from OpenAlex

Private clubs have existed for as long as people have desired to gather in groups to do things together. It has been suggested that private clubs (and their predecessors) date to the Roman baths but probably pre-date even those. It is doubtful that the Roman baths represented the first time people congregated in groups to socialize, discuss commerce, politics, or just engage in a mutually agreeable activity. Certainly, most agree that the ‘modern’ clubs (in the English speaking world) originated in England, were limited to ‘gentlemen’ and organized for social, political, business and/or pleasure reasons. The concept was then ‘exported’ along with ex-patriots all around the world. Clubs have since evolved to the point where they exist in countries around the world although they are embraced to a greater or lesser extent in different places. Examples of private clubs can be found in such countries as England (and the greater UK), Ireland, the United States, Canada, Australia and New Zealand, South Africa, Switzerland, Hong Kong, India, Pakistan, Japan, Singapore, and the UAE. Perhaps no country has adopted the idea of clubs as much as the USA, where they have evolved into a veritable industry, are protected by law, and number into the thousands. Humans, being social creatures, long to spend quality time with others – ‘others’, historically, representing those of their own kind. Perhaps it is for this reason that clubs have, rightly or wrongly, developed a reputation for being discriminatory. People generally find benefits from spending time with others. These benefits may accrue in many forms, including personal, professional, and political.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.025
GPT teacher head0.268
Teacher spread0.244 · 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