Comments from the National Center for the Study of Collective Bargaining in Higher Education and the Professions in Response to Proposed NLRB Rule Concerning Graduate Assistants and Other Student Employees
Bibliographic record
Abstract
These are public comments submitted by National Center for the Study of Collective Bargaining in Higher Education and the Professions, Hunter College, City University of New York in response to a proposed NLRB rule that would exclude student employees from coverage under the National Labor Relations Act (NLRA). The comments include information and data showing that the proposed rule would exclude from NLRA coverage 81,390 graduate assistants working at 518 private institutions in occupations that other federal agencies treat as distinct from the classification of graduate student. The comments also present a half-century of history and legal precedent concerning collective bargaining by graduate assistants and other student employees under state constitutions and collective bargaining laws in 14 states and in Canadian provinces. The authors analyze the bargaining unit composition and terms of 42 current collective bargaining agreements in the higher education industry involving graduate and undergraduate student employees. The most common contract provisions (100%) address wages and grievance-arbitration procedures. The next most common provisions are non-discrimination, and terms of appointment clauses, which are found in 41 agreements (97.62%), followed by management rights and union security provisions contained in 40 agreements (95.24%). Over 90% of the 42 agreements address health care benefits (39), health and safety (38), union access (38), and no-strike clauses are included in over three-quarters of the agreements (32). More than 80% of the contracts have provisions concerning employee leave (37), workload (35), and workplace discipline (35). Academic freedom is specifically addressed in over 30% of the agreements, and intellectual property is a negotiated topic in over a quarter of the contracts. Retirement is a subject in 19% of the contracts. The authors urge the NLRB to closely examine the submitted data, empirical evidence, and precedent. The primary evidence should be the negotiated terms in the current collective bargaining agreements, the experiences of administrators and labor representatives who have bargained and administered those contracts, and the half-century of experience with collective bargaining concerning graduate assistants and other student employees.
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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.091 | 0.044 |
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".