A case study in Gantt charts as historiophoty: A century of psychology at the University of Alberta.
Bibliographic record
Abstract
History is typically presented as historiography, where historians communicate via the written word. However, some historians have suggested alternative formats for communicating and thinking about historical information. One such format is known as historiophoty, which involves using a variety of visual images to represent history. The current article proposes that a particular type of graph, known as a Gantt chart, is well suited for conducting historiophoty. When used to represent history, Gantt charts provide a tremendous amount of information. Furthermore, the spatial nature of Gantt charts permits other kinds of spatial operations to be performed on them. This is illustrated with a case study of the history of a particular psychology department. The academic year 2009-2010 marked the centennial of psychology at the University of Alberta. This centennial was marked by compiling a list of its full-time faculty members for each year of its history. This historiography was converted into historiophoty by using it as the source for the creation of a Gantt chart. The current article shows how the history of psychology at the University of Alberta is revealed by examining this Gantt chart in a variety of different ways. This includes computing simple descriptive statistics from the chart, creating smaller versions of the Gantt to explore departmental demographics, and using image processing methods to provide measures of departmental stability throughout its history. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".