Bibliographic record
Abstract
Abstract This book is a succinct introduction to the orienting of attention. Richard Wright and Lawrence Ward describe the covert orienting literature clearly and concisely, illustrating it with numerous high-quality images, specifically designed to make the challenging theoretical concepts accessible. The book begins with an historical introduction that provides a great deal of information about orienting, much of which will be new even to seasoned researchers. Wright and Ward then systematically describe the development of various experimental paradigms that have been devised to study covert orienting, and the theoretical issues raised by this research. One trend that they analyse in detail is the progression from relatively simple models of spatial attention (attention spotlight and zoom lens models) to an integrative computational framework based on a concept called the ‘activity distribution’. They also present a comprehensive survey of cognitive neuroscience research on the brain mechanisms underlying spatial attention shifts, as well as a chapter summarising recent research on crossmodal attention shifts, and elucidating the links between attention orienting in the visual, auditory, and tactile domains. In the Epilogue they offer a concise summary of the book, and develop preliminary frameworks for understanding the relationship between spatial attention and orienting in response to social cues (social cognitive neuroscience) and for describing the evolution of covert orienting. Orienting of Attention provides a systematic survey that is ideal for those looking for an accessible introduction to the field and also for students and researchers who want a state-of the-art overview.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.015 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".