McClure and Samuels’ Study on Information Sources Used for Decision Making and the Connection to Organizational Climate Still Resonates Today
Bibliographic record
Abstract
A Review of:
 McClure, C. R., & Samuels, A. R. (1985). Factors affecting the use of information for academic library decision making. College & Research Libraries, 46(6), 483-498.
 
 Abstract
 
 Objective - To investigate the use of information sources for decision making within academic libraries; specifically looking at what sources of information are used, whether information use is related to organizational climate, and what organizational factors lead to optimal information use in decision making.
 
 Design - Cross-sectional survey on a random sample of libraries.
 
 Setting - 18 medium to moderately large academic libraries from across the United States.
 Subjects - 356 academic librarians holding a variety of positions and levels of responsibility within their organizations. 
 
 Methods - A questionnaire was mailed to participants in order to measure relationships between four main variables: information acquisition, information dissemination, information evaluation, and library climate. All instruments were validated and tested for reliability. Participants were given 10 library decision situations to consider, together with a list of potential information sources to inform the decision, and then choose which information source they would use primarily in each situation. Participants’ perception of their library climate was measured with five scales covering innovation, support, freedom, democratic governance, and esprit. 
 
 Main Results - The study found that academic librarians prefer internal sources of information, such as interpersonal communication with library staff, and library committees, for making decisions. However, paraprofessional staff members were not seen as meaningful sources of information within this grouping. The participants rarely chose to consult external information sources, such as other professionals outside of the library, or library users. Information sources such as conducting research, continuing education, past experience, or personal opinion were not found to be important to the participants’ decision making. Written documents such as articles, books, and brochures were also seldom used. Democratic governance was the organizational climate dimension found to be most closely linked to information dissemination.
 
 Conclusion - The authors conclude that the study suggests that academic librarians are not using a full complement of information sources to assist with their decision making, and that the “information that is used tends to be ‘opinion-based’ rather than empirically based” (p. 495). Proximity of information plays a role, with information that is closer and easier to obtain being used more frequently. The authors strongly stress, with concern, that, “current academic library decision-making processes encourage ineffective activities since they preclude or limit clientele input, empirical research, and additional environmental input” (p. 495).
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How this classification was reachedexpand
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.358 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".