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Source changed 2026-10-31 05:42:14 UTC · snapshot created 2026-10-31 05:43:13 UTC · last check 2026-10-31 11:05:10 UTC

GOALS.Source:2 - Contemporary contributions and their limits

  • Butler, Zimmermann and Bird, Objectives and Key Results in Software Teams: Challenges, Opportunities and Impact on Development, preprint 2023 / ICSE-SEIP 2024: one-company interviews and survey expose formulation, data and neighboring-goal visibility difficulties. GOALS.5 and GOALS.9 retain these practical questions; the design and self-report limits prevent a universal causal conclusion.
  • Gollwitzer and Sheeran, Psychology of Planning, 2025: the conditional human planning contribution is used in GOALS.6:4.3. The task and person’s conditions govern its use.
  • Riddell and colleagues, Goal adjustment, online 2025 / volume 2026: synthesis distinguishes disengagement, reengagement and flexibility. Heterogeneity, study designs and publication-bias concerns limit broad effect claims. GOALS.4 and GOALS.6 retain adjustment as a choice requiring its own grounds.
  • Islam and colleagues, All pain and no gain, 2024: a school trial distinguishes reported effort from test results. GOALS.2 retains that conceptual caution while deriving workplace criteria from the actual work.
  • Wowerath, Engaging the entire organization, online 2025 / volume 2026: interviews and documents from one early pilot inform participation and integration questions. They do not establish a universal success percentage or long-term effect.
  • Altan, Guney and Uler, Goal Setting and Feedback: The Power of Joint Use, 2026: the studied interaction of employer goals and feedback concerns an experimental effort setting. Its worker costs and employer benefit require separate interpretation; it supplies no universal OKR or welfare prescription.
  • Chen and colleagues, Are We On Track?, CHI 2025: a small prototype study distinguishes passive cues and active reflection prompts. It motivates comparing interruption with useful action in GOALS.5, rather than a claim that an AI meeting monitor generally improves work.
  • Tankelevitch and Rintel, Goals as First-Class Abstractions in Human–AI Collaboration, 2026: a design position motivates explicit meaning, history and revision in GOALS.7. Current system behavior still needs its own technical basis.
  • OpenAI, Detecting misbehavior in frontier reasoning models, 10 March 2025: coding experiments expose reward exploitation under particular training and evaluation conditions. GOALS.7 separates the wanted result from the optimized reward and requires an adequate basis for completion evidence.
  • OpenAI, Foundations for trustworthy third-party evaluations, 29 May 2026: evaluation guidance relates claims to the actual model, scaffolding, environment, resources and assessment. GOALS.7 retains these configuration conditions when interpreting evidence or changing the arrangement.

These sources answer different questions. A current publication can report older data, and a current interface can differ from the one described. Use current product documentation for runtime capabilities and the relevant professional source for a stronger psychological, organizational or causal claim.