How Advances in Digital Technologies Reconfigure Organizational Coordination Processes
Bibliographic record
Abstract
Today’s digital technologies have unique material, cultural, and economic characteristics that make them fundamentally different from technologies of decades past. While the increasingly important role of digital technologies in today’s organizations is hard to deny, scholars have much to learn, empirically and theoretically, about how digital technologies affect organizational processes. This symposium will focus on how advances in digital technologies are prompting changes in how work is coordinated inside organizations. It brings together a diverse set of papers representing different theoretical orientations, levels of analysis, and empirical settings–each with the question of how coordination processes change in the migration of phenomenon from “offline” to “online.” The goal of the symposium is to integrate these approaches to make progress on a multi-level understanding of how digital technologies impact work, and what coordination requires in the digital age. Social Tools and Leaky Knowledge: A Solution to the Search-Transfer Problem Presenter: Paul Leonardi; UC Santa Barbara Putting the openness to work: How knowledge workers navigate digital technologies Presenter: Emmanuelle Vaast; McGill U. Presenter: Alain Pinsonneault; McGill U. Spanning Boundaries for Open Innovation: Digital Platforms versus Organizational Teams Presenter: Natalia Levina; New York U. Presenter: Anne-Laure Fayard; New York U. Reconfiguring Coordination for Social Media: Digital Disruption in the Advertising Industry Presenter: Emily Truelove; Massachusetts Institute of Technology
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".