Bibliographic record
Abstract
The proposed research seeks to examine the effectiveness of a novel application of scheduling called an unschedule. In an unschedule, the emphasis is paradoxically on scheduling enjoyable activities before scheduling work. According to the promoter of this method, Neil Fiore (2007), when we neglect to prioritize enjoyable activities, as often happens in traditional scheduling, our workload becomes tedious to the point of procrastinating. In this study, undergraduate participants will begin with a two-week baseline period in which they record the amount of time they spend studying. Participants will then be assigned to one of three conditions: (1) a control group that will employ the traditional method of scheduling their studying first, (2) an unscheduled group that will schedule their fun activities first, and (3) an unscheduled plus 30-minute group that will use unscheduling as well as short 30-minute study sessions (which Fiore also suggests in order to reduce task aversiveness). The hypotheses are that the participants who are in the unscheduled conditions, and especially those in the unscheduled plus 30-minute condition, will increase their time spent studying and report being less distracted by temptations, thereby, decreasing their overall tendency to procrastinate. Discipline: Psychology Honours Faculty Mentor: Dr. Russ Powell
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".