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Record W3196058345

Call for Papers (Manufacturing Phobias)

2010· paratext· en· W3196058345 on OpenAlexaff
Hisham Ramadan

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typeparatext
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsKwantlen Polytechnic University
Fundersnot available
KeywordsPhobiasPhenomenonPoliticsPsychologySocial psychologyPublic relationsPolitical scienceLawEpistemologyAnxiety
DOInot available

Abstract

fetched live from OpenAlex

A Call for Papers: Various groups have recognized that hope and fear are very powerful driving forces capable of moving nations and shaping its actions. They have utilized both of these emotions to achieve their target, notwithstanding the negative impact on society as a whole. This phenomenon is not new. However, the current trend in this phenomenon is worth investigating in the form of a book containing a number of essays each of which expounds a different aspect of such phenomena. This is, by nature, an interdisciplinary book. Scholars from different disciplines are invited to contribute to this volume. The purpose of the book is not to investigate phobias as a psychological disorder. Rather it aims to focus on how, why, and by what means, social phobias, as an industry, are created by special interest groups such as religious leaders, politicians and financial sector leaders to target the most vulnerable in our society to achieve what is , indeed, impossible to achieve by ethical means. Topics may include but are not limited to: • phobias and economy/ economical factors • political phobias • religious phobias • cultural phobias • racial phobias A contract for this book will be sought once a comprehensive book proposal is completed after compiling proposals for essays. We are sure, given our publication record, that the book shall be published by major publisher. The book will consist of 7-8 essays. Each essay between 12,000-15,000 words in length including a reference list. Please send a 300 word proposal or full-length essay, as Word doc attachments, to Dr Hisham Ramadan and Dr. Jeff Shantz via email at hisham.ramadan@kwantlen.ca, Jeffrey.Shantz@kwantlen.ca by Dec 30, 2010.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, 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 score0.342
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.291
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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