Bibliographic record
Abstract
Rating RateMYProfessors.com N. Katherine Hayles (bio) and Nicholas Gessler (bio) In these information-rich and data-happy times, ratings are everywhere. Buyers and sellers rate each other on eBay; car dealers send out rating cards to buyers; Amazon sends e-mail to customers asking them to rate their purchase experiences; dating services ask clients to rate themselves as well as one another. Why shouldn't students join in the fun and rate their professors? We think professor rating sites perform a valid service in disseminating information about professors that help students make informed decisions about what courses they will or will not take. Moreover, rating sites can potentially assist professors by providing a feedback loop between student opinion and professorial performance, which could be useful in improving teaching techniques. But rating services beware; turn around is fair play. Rating services are not created equal. Below are our ratings for RateMyProfessors.com. (Disclaimer: As with any rating service, one must consider the motives of those who ask the questions and those who supply the answers, including this review. Both of us are on the faculty at the University of California, Los Angeles, one as a tenured professor and another as a lecturer. Both of us have been rated favourably at ucla.professors.com. One has been favourably rated at RateMyProfessors.com; the other is unrated at that site.) [End Page 6] 1. The Seriousness Factor What happened to course content? Is "Clarity" really the same as providing tools for critical analysis, imparting information, and laying the foundation for professional knowledge and methodologies? Although "Clarity" might be defended as a purposely vague category aimed to elicit specific comments from students, in our view "Content" would be a better choice. Clearly presented rubbish is still rubbish. 2. The Laziness Factor Granting that easiness may be a valid consideration for students who are already carrying a heavy course load, and recognizing that, on RateMyProfessors, scores in this category do not contribute to an instructor's overall rating, we still feel that the presence of "Easiness" as one criterion among four throws a troubling emphasis on doing as little as possible for a given course credit. "Ease of Learning" might be a better (or additional) category, since it introduces considerations not primarily of workload but of how accessibly complex material has been presented. 3. The Sleaze Factor Are chili peppers a valid criterion for effective teaching? In an earlier incarnation of the site, the FAQ provided a link to a New York Times article saying that surveys show good-looking and sexy professors get higher course ratings than average-looking (not to mention downright ugly) ones—hardly a justification for equating sexiness with a good education but, merely, an indication of status quo practices. In the site's current incarnation, the Times link is gone, but chili peppers remain front and centre. Of course, "Hot" might be understood to allude not primarily to physical characteristics but to a captivating manner, a lively style of presentation, and a vivid ability to convey the excitement of intellectual challenges. These are validly related to teaching and should be considered. 4. The Consumerist Factor The site's FAQ states that the site owners regard students as consumers. This business orientation provides the primary justification for the site. Yet there are important differences between students and consumers that make this a badly flawed comparison. Corporations have a legal obligation to produce profit for their shareholders, and businesses have an economic incentive to do the same for their owners. The exigencies of the market dictate that corporate processes are dominated by this imperative. Pleasing [End Page 7] consumers sells products, and selling products produces profit. Research universities and liberal arts colleges, on the other hand, are not-for-profit ventures. They are not in the business of making profits but of creating, disseminating, and preserving knowledge. Although patents, inventions, and products may result from the creation of knowledge, this is not their primary goal. Large research universities have very big research expenses, and this necessarily requires that they actively seek grants and other income-producing vehicles. Although priorities sometimes get muddled, these should be sought in order to produce new...
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.823 | 0.837 |
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".