Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.300 | 0.137 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".