Cognitive Research in Information Systems
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
The existence and significance of cognition in organizations and its influence on patterns of behaviour in organizations and organizational outcomes are increasingly accepted in information systems (IS) research (Barley, 1986; DeSanctis & Poole, 1994; Griffith, 1999; Griffith & Northcraft, 1996; Orlikowski, 1992, 1994 #208). However, assessing the commonality and individuality in cognition and eliciting the subjective understanding of research participants either as individuals or as groups of individuals remain a challenge to IS researchers (Orlikowski & Gash, 1994). Various methods for studying cognition in organizations have been offered - for example, clinical interviewing (Schein, 1987), focus groups (Krueger, 1988), discourse-based interviewing (Odell, Goswami & Herrington, 1983). This article proposes that cognition applied to making sense of IT in organizations can also be explored using Kelly’s (1955) Personal Construct Theory and its methodological extension, the Repertory Grid (RepGrid). The RepGrid can be used in IS research for uncovering the constructs research participants use to structure and interpret events relating to the development, implementation, use and management of IS in organizations. In the context of this article, cognition is considered to be synonymous with subjective understanding: “the everyday common sense and everyday meanings with which the observed human subjects see themselves and which gives rise to the behaviour that they manifest in socially constructed settings” (Lee, 1991, p. 351). Research into cognition in organizations investigates the subjective understanding of individual members within the organization and the similarities and differences in the understandings among groups of individuals (Jelinek & Litterer, 1994; Porac & Thomas, 1989). In IS research, it is the personal constructs managers, users and IS professionals use to interpret and make sense of information technology (IT) and its role in organizations. The discussion here outlines the myriad of ways the RepGrid can be employed to address specific research objectives relating to subjective understanding and cognition in organizations. It illustrates, from a variety of published studies in IS (see Table 1), the flexibility of the RepGrid to support both qualitative and/or quantitative analyses of the subjective understandings of research participants.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.009 |
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