Bibliographic record
Abstract
As a result of the power of corporations and the impact on society of corporate activity, more attention is focused on the role of business in serving the needs of society (Tichy, McGill, & St. Clair, 1997). From traditional philanthropy to large-scale initiatives, many corporations now invest their resources and people in acts of so-called corporate responsibility (Tichy, McGill, & St. Clair, 1997). Along with the potential benefits to society of such acts comes a consideration of the potential competitive advantages for corporations in acting sociably responsible. In particular, a sociably responsible reputation can play a role in recruitment as potential employees are more likely to pursue jobs in organizations with more responsible reputations (Greening & Turban, 2000; Backhaus, Stone & Heiner, 2002). Although social responsibility can make corporations more attractive, we need a better understanding of how individual characteristics or dispositions of potential employees increase the likelihood that jobs are favored in corporations that are sociably responsible. In particular, due to the impassioned debate surrounding corporate responsibility (Boal & Perry, 1985), what is the role of individual emotion when considering employment options? This question has implications for corporations, in terms of recruitment and organizational objectives, and subsequently for society as a whole.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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; both teacher heads agree on what is shown here.
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".