Plan and Situated Action Relationship as a Function of Activity Category: An Experimental Approach - eScholarship
Bibliographic record
Abstract
Plan and Situated Action Relationship as a Function of Activity Category: An Experimental Approach Walid Bahamdan Department of Management Sciences, 200 University Avenue West Waterloo, Ontario, N2L 3G1, CANADA Rob Duimering Department of Management Sciences, 200 University Avenue West Waterloo, Ontario, N2L 3G1, CANADA Abstract: Plan and situated action relationship has been an active area of debate in recent years in various fields of study yet such relationship has a propensity for ambiguity. It would be a limited/desperate argument to claim that plans can capture every level of detail. Needless to say, a model cannot exceed or equal reality. Given that a clear mismatch/incongruence or gap exists between plans and actual events, how do people experience this gap and how do they act accordingly? The proposed framework integrates the field theory of the here-and-now action developed by Kurt Lewin (1936), with both the prototype and basic-level category theories developed primarily by Rosch (1978). Lewin’s theory captures the dynamic properties of situations whereas Rosch’s categorization theories capture typifications of the human experience. More specifically, plans are conceived as an activity category-set of possibilities of some future events by which plans have categorical relationships with future actions.
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 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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".