Illuminating the Signals Job Seekers Receive from an Employer's Community Involvement and Environmental Sustainability Practices: Insights into Why Most Job Seekers Are Attracted, Others Are Indifferent, and a Few Are Repelled
Bibliographic record
Abstract
Evidence shows that job seekers tend to be attracted to employers known for their corporate social responsibility (CSR), but relatively little is known about the underlying psychological processes. Moreover, the literature is silent about whether and why some job seekers are unaffected, or even repelled by, an employer's CSR. We conducted a substantive replication of recent empirical support for three signal-based mechanisms by adapting the experimental manipulation used in a prior study while employing an alternative approach to analyzing a distinctly different type of data. We also extended prior work by examining other possible explanatory mechanisms and exploring potentially negative reactions to CSR. Using signaling theory as an overarching framework, we assessed research questions and tested hypotheses grounded in theories of employee recruitment and the psychology of CSR, specifying how an employer's CSR practices send signals from which job seekers draw inferences about unknown working conditions, thereby affecting their attraction to the employer. Study participants (N = 108) reviewed the webpages of two hiring companies and responded to open-ended questions about each employer. We content-analyzed written responses pertaining to one employer's webpages in which we embedded an experimental manipulation of information about the employer's community involvement or its environmentally sustainable practices. The results supported hypotheses that corroborate prior evidence for the "perceived value fit" and "expected employee treatment" mechanisms, and provided some, but relatively limited, support for the "anticipated pride" mechanism. Assessment of research questions highlighted previously undiscovered signal-based mechanisms that might help explain job seekers' attraction to CSR (e.g., inferences about the employer's positive work environment and financial standing, and the nature of its employees). Results also showed that a few people were less attracted because of the employer's CSR practices. Analyses among those individuals, combined with one-third of the sample who reported their attraction was unaffected by the employer's CSR, provided insights about when and why CSR fails to enhance attraction, such as when job seekers focus on other priorities, or are deeply skeptical and cynical about the employer's CSR. We discuss the implications for advancing a signal-based theory of CSR and employee recruitment, and recruitment practice.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".