An Empirical Examination of the Relationship Between Adult Attention Deficit, Cooperative Conflict Management and Efficacy for Working in Teams
Bibliographic record
Abstract
A recent national survey of the US workforce suggests that adult attention related disorders are producing a wide range of negative outcomes in the workplace. The symptoms typically associated with the disorder (difficulties with activation, concentration, effort, emotional interference and accessing memory) suggest that team work may represent a problematic situation for adults with the disorder. Subjects were one hundred and fifty‐five student teams (subjects=628) from universities in both Canada and the United States. The study begins by confirming a hypothesis arising out of previous qualitative research that team members with adult attention deficit have relatively greater difficulty with necessary but uninteresting tasks. The hypothesis that team members with the disorder will be extraordinarily reliant on their teammates was also supported. The need to secure situations of particular fit, and to do so without undermining the support of fellow teammates, suggests that cooperative conflict management styles are especially important for clinical AAD vs. non‐clinical team members. The specific hypotheses, that cooperative styles (problem solving and compromising) are especially important for producing positive team experiences/expectations and efficacy for working in teams, were supported. Future research needs to sample more workplace teams.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".