Consequences of the Internet for self and society : is social life being transformed?
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.
Bibliographic record
Abstract
Part I: Introduction:1. Introduction to the issue: John A. Bargh, Department of Psychology, New York University.Part II: The Internet and the Individual:2. Relationship Formation on the Internet: What's the Big Attraction?: Katelyn Y. A. McKenna, Amie S. Green, & Marci E. J. Gleason, Department of Psychology, New York University.3. Can You See the Real Me? Activation and Expression of the 'True self' on the Internet: John A. Bargh, Katelyn Y. A. McKenna, & Grainne M. Fitzsimons, Department of Psychology, New York University.4. Internet Paradox Revisited: Robert Kraut, Sara Kiesler, Bonka Boneva, Jonathon Cummings, Vicki Helgeson, & Anne Crawford, Department of Human-Computer.Interaction, Carnegie-Mellon University.5. Internet Use and Well-Being in Adolescence: Elisheva F. Gross, Jaana Juvonen, & Shelly L. Gable, Department of Psychology, University of California - Los Angeles.Part III: The Internet and the Organization:6. When are Net Effects Gross Products? The Power of Influence and the Influence of Power in Computer-Mediated Communication: Russell Spears & Tom Postmes, Department of Social Psychology, University of Amsterdam Martin Lea, Department of Psychology, Manchester University Anka Wolbert, Department of Social Psychology, University of Amsterdam.7. Negotiating via Information Technology: Theory and Application: Leigh Thompson, Kellogg Graduate School of Business, Northwestern University, Janice Nadler, Northwestern University and American Bar Foundation.Part IV: The Internet and Government:8. Civic Culture Meets the Digital Divide: The Role of Community: Electronic Networks: Eugene Borgida, John L. Sullivan, Alina Oxendine, Melinda S. Jackson, Eric Riedel, & Amy Gangl, Departments of Law and Psychology, University of Minnesota.9. Dark Guests and Great Firewalls: The Internet and Chinese Security Policy: Ronald J. Deibert, Department of Political Science, University of Toronto.Part V: Methodological Techniques and Issues:10. eResearch: Ethics, Security, Design, and Control in Psychological Research on the Internet: Brian Nosek & Mahzarin R. Banaji, Department of Psychology, Yale University, Anthony G. Greenwald, Department of Psychology, University of Washington.11. Studying Hate Crime with the Internet: What Makes Racists Advocate Racial Violence? Jack Glaser & Jay Dixit, Goldman School of Public Policy, University of California - Berkeley Donald Green, Department of Political Science, Yale University.Part VI: Concluding Perspective:12. Is the Internet Changing Social Life? It Seems the More Things Change, the More They Stay the Same: Tom R. Tyler: Department of Psychology, New York University.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it