Woods v. Bisignano

NOT FOR PUBLICATION FILED UNITED STATES COURT OF APPEALS MAY 16 2025 MOLLY C. DWYER, CLERK U.S. COURT OF APPEALS FOR THE NINTH CIRCUIT RONALD WOODS, No. 24-1729 D.C. No. Plaintiff - Appellant, 5:22-cv-02019-PD v. MEMORANDUM** FRANK BISIGNANO,* Commissioner of Social Security, Defendant - Appellee. Appeal from the United States District Court for the Central District of California Patricia A. Donahue, Magistrate Judge, Presiding Submitted May 14, 2025*** Pasadena, California Before: IKUTA, R. NELSON, and LEE, Circuit Judges. Concurrence by Judge R. NELSON. After an administrative law judge (ALJ) found that jobs matching Ronald * Frank Bisignano is substituted as Commissioner of Social Security pursuant to Fed. R. App. P. 43(c)(2). ** This disposition is not appropriate for publication and is not precedent except as provided by Ninth Circuit Rule 36-3. *** The panel unanimously concludes this case is suitable for decision without oral argument. See Fed. R. App. P. 34(a)(2). Woods’ capabilities existed in substantial numbers in the national economy, the ALJ denied Woods’ claim for disability benefits. The district court affirmed. Woods appeals. We have jurisdiction under 42 U.S.C. § 405(g), and we review the agency’s factual findings for substantial evidence. Id. We affirm. 1. Substantial evidence supports the ALJ’s job estimates. The ALJ adopted its estimates from the testimony of a vocational expert. The expert has extensive relevant experience, and Woods does not dispute that she is qualified. And while the expert referenced the Occupational Employment Quarterly, which Woods claims is unreliable, see Kilpatrick v. Kijakazi, 35 F.4th 1187, 1194 (9th Cir. 2022), the expert also relied on OccuBrowse+ and Job Browser Pro, the reliability of which Woods does not dispute. Thus, the expert’s testimony is the type of evidence that “a reasonable mind might accept” as adequate support for the ALJ’s job estimates. Biestek v. Berryhill, 587 U.S. 97, 102–03 (2019) (quotation omitted); see also Ford v. Saul, 950 F.3d 1141, 1160 (9th Cir. 2020). 2. When a claimant submits job estimates that conflict with an expert’s, Ninth Circuit precedent requires the ALJ to resolve the conflict. Kilpatrick, 35 F.4th at 1193–94. The ALJ must address conflicts, however, only when the claimant’s estimates are “significant” and “probative.” Id. Woods did not use all the same sources or methodology as the expert, and Woods has not shown that he has any expertise in estimating national job numbers. See id. at 1194; Wischmann v. 2 24-1729 Kijakazi, 68 F.4th 498, 506–07 (9th Cir. 2023). Thus, Woods’ alternative estimates are not probative, and the ALJ did not need to explain why it credited the expert’s estimates over Woods’ alternatives. 3. Woods argues that Social Security Ruling 00-4p1 is invalid because it conflicts with 20 C.F.R. § 404.1566(d). There is no conflict. See Shaibi v. Berryhill, 883 F.3d 1102, 1109 n.6 (9th Cir. 2017). The regulation requires ALJs to take notice of reliable job estimates, and SSR 00-4p requires ALJs to ensure that expert testimony is consistent with the Dictionary of Occupational Titles. SSR 00-4p does not prevent ALJs from taking notice of other reliable job information. AFFIRMED. 1 SSR 00-4p has been rescinded, but its replacement is not retroactive. SSR 24-3p. 3 24-1729  FILED Woods v. Bisignano, No. 24-1729 MAY 16 2025 MOLLY C. DWYER, CLERK R. Nelson, J., concurring: U.S. COURT OF APPEALS Estimating the number of jobs in the national economy is not an exact science. Ronald Woods argues that absent special justification, it’s unreasonable for vocational experts to rely on the equal-distribution method. The majority correctly resolves Woods’ appeal without deciding whether to adopt his rule. I write separately to explain why we should reject his rule in a future case. Substantial evidence is evidence that “a reasonable mind might accept as adequate to support a conclusion.” Biestek v. Berryhill, 587 U.S. 97, 102–03 (2019) (quotation omitted). Under this standard, vocational expert testimony is “ordinarily sufficient by itself” to support an agency’s job estimates. Ford v. Saul, 950 F.3d 1141, 1160 (9th Cir. 2020). That’s true even if the expert doesn’t disclose her methodology or data. Bayliss v. Barnhart, 427 F.3d 1211, 1218 (9th Cir. 2005); Biestek, 587 U.S. at 105. After all, it’s generally reasonable to credit expert testimony on matters within the expert’s expertise. Of course, there are exceptions. Perhaps the expert is unqualified. Or perhaps the expert uses a facially implausible methodology. In the Seventh Circuit, before experts may use the equal-distribution method, they must justify that approach. Chavez v. Berryhill, 895 F.3d 962, 965 (7th Cir. 2018). Otherwise, the Seventh Circuit deems it unreasonable to credit their equal-distribution estimates. Id. 1  Woods asks us to apply the Seventh Circuit’s rule here. “Where [Woods] goes wrong, at bottom, is in pressing for a categorical rule.” Biestek, 587 U.S. at 108. Determining whether expert testimony is substantial evidence depends on the specifics of the record and testimony. Id. Because this determination proceeds “case-by-case,” there is no “categorical rule,” id., that makes expert testimony “per se unreliable,” Ford, 950 F.3d at 1159. This case shows why. In some cases, the assumptions underlying the equal- distribution method are “improbable.” Kilpatrick v. Kijakazi, 35 F.4th 1187, 1193 (9th Cir. 2022). But in other cases, those assumptions make sense. When a labor statistic is distributed among highly similar job titles, it makes sense to assume that each job title reflects a roughly equal share of the overall statistic. In other cases, the expert testimony may have “sufficient indicia of reliability”—e.g., strong qualifications or experience—that it’s reasonable to credit the testimony even though the expert never justifies the equal-distribution method. See Biestek, 587 U.S. at 103, 107. In other words, determining whether expert testimony is substantial evidence depends on the circumstances of the case—and that remains true when it comes to the equal-distribution method. Woods’ per se rule would hold otherwise. So in a future case, we should reject his proposed rule. 2