Bibliographic record
Abstract
Do you pay attention to the differences between extroversion and introversion? It can be fascinating to consider who is and is not aware of the distinction between the two, as well as the significant formative role they both play in daily perceptions and interactions. In my experience, more often than not it is the introverts who recognize and appreciate the difference, while too many extroverts remain unaware. In Quiet: The Power of Introverts in a World That Can’t Stop Talking(2012), Susan Cain reminds us of the potency and power of the gift of introversion. She challenges her readers to recognize and celebrate the unique insights and contributions that may be latent in communities and organizations—present, but hidden from view, and likely to remain so unless given the space to flourish and to find a voice. She also suggests that creating a space for the introvert voice may bring unforeseen blessings to an organization or community.
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.037 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".