An exploratory study on information work activities of competitive intelligence professionals
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
Competitive intelligence (CI) can be loosely defined as the process by which an organization legally and systematically collects, organizes, analyzes, and disseminates the information about its competitive environment. Notwithstanding the growing interest in CI, there are few empirical investigations on the work activities of CI professionals. This research addresses three basic questions: Who are CI professionals, which tasks and activities are they engaged in and how do they go about them, and what factors constrain their performance and completion of these tasks and activities? Twenty-eight CI professionals across Canada participated in the study from 24 different organizations, representing 16 specific industries. These CI professionals include various intelligence managers and analysts, market researchers, strategic advisors, and information specialists, representing two main groups: business professionals and information professionals. Their major goals are to heighten awareness of the competitive environment in which their organizations compete and to enhance decision making by their various clients. To achieve these goals, they engage in 10 general classes of activities: news scanning and monitoring; project management; responding ad hoc requests; communicating with various stakeholders; preparing CI products/deliverables; perusing and evaluating various materials; writing and editing diverse documents; coaching and training other staff for CI; undertaking training themselves; and administrative, non-CI, and sundry other activities. Among them, most of time is allocated to preparing CI products or deliverables, communicating with various stakeholders, and email processing and news scanning. Most of the information needs of the participants are not personal but derive from their organizational needs and clientele. The information seeking behavior of the participants can be situated on four axes: cyclical and noncyclical, reactive and proactive, linear and
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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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